Top AI Engineer Staffing Companies in 2026
Ranked reviews of 29 companies that place machine learning engineers in your team, sorted by the roles they can fill and by who runs the technical screen.
Which AI engineer staffing company is best?
Short answer: Tensorway is the top pick when you want senior AI engineers screened by other engineers. deepsense.ai has the deepest research bench, Toptal is the quickest route to one vetted freelancer, and Azumo has the lowest published rate.
- Best overall: Tensorway – Senior AI engineers run a code review and a specialization-specific task on every candidate
- Best for a senior ML researcher who also ships to production: deepsense.ai – A research-heavy bench of about 120 employed AI specialists with ten years of production work
- Best for one vetted freelance specialist, fast: Toptal – Multi-stage screening that ends with interviews by senior engineers and a test project
- Best for LLM agent engineers: Vstorm – A team that works almost entirely on LLM agents and RAG
- Best for ML engineers on U.S. hours at a low rate: Azumo – The lowest published hourly band on this page with full U.S. time-zone overlap
- Best for a refundable 30-day trial: Index.dev – A 30-day trial with full refund on every placement
How do the 29 top AI engineer staffing companies compare?
All 29 companies in rank order. Few publish rates, so the pricing column describes how each one bills.
| Company | Best for | Pricing model | Min. engagement | Rating |
|---|---|---|---|---|
| Tensorway Editor's pick | CTOs who want an engineer, not a recruiter, to have vetted every candidate before the first interview | Monthly rate per full-time dedicated engineer; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request | Not disclosed | |
| Teams that need a senior ML researcher who can also put models into production | Team extension billed monthly per engineer; projects quoted separately; rates on request | Not published | | |
| Engineering leads who need one senior freelance ML specialist quickly and can pay a premium | Freelance hourly or weekly rates set per engineer; no-risk trial period; rates on request | Not published | | |
| European companies that want a vetted ML or data engineer on European working hours | Hourly rate per developer billed monthly; full-time or part-time; rates on request | Not published | | |
| Product teams that need a computer-vision or NLP engineer with shipped work in that exact area | Dedicated team billed monthly; projects from under $50,000 to over $100,000 (Clutch); rates on request | Not published | | |
| Enterprises that need many AI roles filled at once by one AI-only supplier | Elastic Staffing billed per specialist; consulting quoted separately; rates on request | Not published | | |
| Banks and insurers that need agent or LLM engineers who have worked under financial regulation | Monthly team or per-engineer billing; projects quoted separately; rates on request | Not published | | |
| Startups that want a 30-day refundable trial before committing to a remote ML engineer | Monthly rate per engineer; direct-hire fee option; 30-day trial with refund; rates on request | Not published | | |
| Teams whose LLM agent prototype needs engineers who have shipped agents before | $100–$149/hr (Clutch band); team extension or project billing | $10,000+ | | |
| Companies that need many remote ML and data engineers quickly and value speed over hand-picked screening | Monthly or hourly per developer; no public rate card; rates on request | Not published | | |
| Companies building a long-term remote engineering group outside the U.S. that includes some ML roles | Monthly rate per engineer; marketplace and managed options; rates on request | Not published | | |
| Python-heavy teams that want employed senior engineers rather than freelancers | Monthly rate per engineer; $50–$99/hr Clutch band; rates on request | Not published | | |
| Healthcare data teams that need NLP or data scientists familiar with medical data standards | Dedicated team billed monthly; projects quoted separately; rates on request | Not published | | |
| Cost-conscious companies that want mid-level ML engineers from a publicly listed supplier | Monthly per engineer or team; projects quoted separately; rates on request | Not published | | |
| Industrial and automotive companies that need data engineers who know factory data | Monthly per engineer or project fee; rates on request | Not published | | |
| Teams that need an MLOps or computer-vision engineer started within days on a low budget | Monthly per engineer; two-week trial; offshore rates; rates on request | Not published | | |
| U.S. teams on a tight budget that need ML engineers who work their hours | $25–$49/hr (Clutch band); monthly staff augmentation or dedicated team | $10,000+ | | |
| U.S. companies that need ML engineers alongside a larger nearshore software team | Monthly per engineer or team; rates on request | Not published | | |
| Large companies that want ML and data engineers from an established Central European supplier | Monthly per engineer or managed team; rates on request | Not published | | |
| Mid-size companies that want one supplier for ML engineers in both Latin America and Europe | Monthly per engineer or team; rates on request | Not published | | |
| Companies that want to hire Ukrainian ML engineers directly, with an outstaffing option meanwhile | Recruiting fee per hire; outstaffing billed monthly; rates on request | Not published | | |
| Leadership teams that want a part-time senior ML expert for one defined problem | Project or fractional billing; rates on request | Not published | | |
| U.S. startups that want to hire a Latin American ML developer directly | Monthly fee per developer or hiring fee; rates on request | Not published | | |
| U.S. teams that need a managed nearshore squad with an ML engineer in it | Monthly per engineer or squad; rates on request | Not published | | |
| Cost-conscious teams that can write a precise brief for an Eastern European ML hire | Monthly per engineer with a service fee; rates on request | Not published | | |
| AI teams that need many vetted contributors quickly for evaluation or data work | Hourly or monthly per contractor; one-week test option; rates on request | Not published | | |
| AI labs and research teams that need specialist contractors in large numbers | Contractor rate plus platform fee (about 30%, Sacra estimate) | Not published | | |
| Companies hiring permanent data or ML staff in the UK or U.S. through a specialist agency | Placement fee for permanent hires; contractor day or hourly rates; rates on request | Not published | | |
| U.S. companies that want a local agency to recruit ML engineers on contract-to-hire terms | Contract bill rate or placement fee; rates on request | Not published | |
What separates a good AI engineer staffing company from a weak one?
Ask an AI engineer staffing company who runs its technical interview, and the answer sorts the market faster than any ranking. At some firms it is a senior machine learning (ML) engineer who reads the candidate's code and sets a task in the specialty you are hiring for. At others it is a recruiter working from a keyword list, and at a growing number it is software: micro1 and Mercor put every applicant through an AI interviewer first. Any of the three can produce a good hire. Only the first tells you much before your own engineers start spending hours on interviews.
Role coverage is the second filter. Almost every company on this page can find a Python developer who has trained a model. Far fewer can supply someone who has run machine learning operations (MLOps) for a model serving real traffic, tuned a large language model (LLM) for a narrow domain, or shipped computer vision to an edge device. If you need one of those people, ask for two anonymized profiles with that exact experience before you sign. Tensorway, deepsense.ai and InData Labs can answer from their own staff. General networks usually start a search.
Then decide how much continuity you need. Marketplaces such as Toptal, Turing and Mercor are quick, and some of their engineers are excellent, but they are contractors who can move on to the next client. Companies that employ their engineers, such as Uvik and N-iX, trade a little speed for people who stay. For a model your team will maintain for years, that usually outweighs an extra week of lead time.
Which frameworks and clouds does each company's bench cover?
Short answer: PyTorch and the three big clouds are close to universal. LangChain and other agent tooling are where coverage thins out.
| Company | Primary tech stack |
|---|---|
| Tensorway | Python, PyTorch, TensorFlow, Hugging Face, LangChain |
| deepsense.ai | Python, PyTorch, TensorFlow, LangChain, Hugging Face |
| Toptal | Python, PyTorch, TensorFlow, Hugging Face, LangChain |
| Proxify | Python, PyTorch, TensorFlow, scikit-learn, Databricks |
| InData Labs | Python, PyTorch, TensorFlow, OpenCV, Hugging Face |
| Quantiphi | Python, TensorFlow, PyTorch, Google Cloud, AWS |
| Neurons Lab | Python, PyTorch, LangChain, OpenAI, Amazon Bedrock |
| Index.dev | Python, PyTorch, TensorFlow, LangChain, Hugging Face |
| Vstorm | Python, LangChain, LlamaIndex, OpenAI, Anthropic |
| Turing | Python, PyTorch, TensorFlow, OpenAI, LangChain |
| Andela | Python, TensorFlow, PyTorch, OpenAI, AWS |
| Uvik Software | Python, Django, FastAPI, Databricks, Snowflake |
| SciForce | Python, PyTorch, TensorFlow, spaCy, Hugging Face |
| Fusemachines | Python, TensorFlow, PyTorch, OpenAI, AWS |
| Addepto | Python, Databricks, Spark, Azure, AWS |
| Folio3 | Python, TensorFlow, PyTorch, OpenCV, LangChain |
| Azumo | Python, PyTorch, TensorFlow, OpenAI, LangChain |
| BairesDev | Python, TensorFlow, PyTorch, OpenAI, AWS |
| N-iX | Python, Spark, Databricks, AWS, Azure |
| Svitla Systems | Python, PyTorch, LangChain, OpenAI, AWS |
| Data Science UA | Python, PyTorch, TensorFlow, OpenCV, AWS |
| Tribe AI | Python, PyTorch, OpenAI, Anthropic, LangChain |
| Strider | Python, TensorFlow, PyTorch, AWS, Google Cloud |
| Coderio | Python, TensorFlow, PyTorch, AWS, Azure |
| Qubit Labs | Python, TensorFlow, PyTorch, AWS, Azure |
| micro1 | Python, PyTorch, OpenAI, LangChain, AWS |
| Mercor | Python, PyTorch, OpenAI, Anthropic, AWS |
| Harnham | Python, SQL, Spark, AWS, Azure |
| KORE1 | Python, AWS, Azure, Google Cloud, TensorFlow |
How did a company make this list?
Each of the companies ranked for 2026 passed these checks:
- It places engineers. A staffing, team-extension or placement service exists, or client reviews describe one.
- It covers AI roles. At least ML or data engineers, with named frameworks rather than a generic "AI talent" claim.
- Its screening is described. We note whether engineers, recruiters or software run the technical interview.
- The basics check out. Founding year, headquarters and size appear somewhere besides the company's own site, and ownership changes are disclosed.
Top 10 AI engineer staffing companies in 2026
Short reviews of the ten highest-rated companies. Each of the 29 has its own full profile.
1. Tensorway
Editor's pickAI engineers screened by senior AI engineers, not by recruiters
Tensorway is an AI engineering company from Alicante, Spain, founded in 2019, and the people behind its delivery process have been building software for more than twenty years. What sets its staffing service apart is who does the screening. Senior AI engineers review each candidate's code, set a practical task in the exact specialization the client asked for and check how the person communicates, so a CTO receives two or three people who have already passed a technical bar (per company website; independently unverifiable). The roles cover ML, computer vision, NLP, MLOps and RAG work. Smaller published projects include an agent that grades GAMSAT practice essays, invoice extraction for a fintech client and ball-hit detection for a fitness game (per company website; independently unverifiable).
Advantages
- +The technical screen is a code review plus a hands-on task in the role you are hiring for, set by working AI engineers
- +Covers the harder-to-fill roles on this list, including speech, edge computer vision and RAG specialists
- +A two-week trial sprint comes before any longer commitment, and a poor fit is replaced at no cost (per company website)
Things to consider
- -No published rate, so budgeting needs a call
- -The bench is in the low hundreds at most, so it cannot staff twenty seats in a month the way Turing or Andela can
- -AI and ML roles only; a CTO who also needs front-end or mobile engineers will need a second supplier
Best for: CTOs who want an engineer, not a recruiter, to have vetted every candidate before the first interview
A Warsaw research team that lends out ML and MLOps engineers
deepsense.ai has done AI work out of Warsaw since 2014, and its job listings describe a team of about 120 AI specialists who have delivered more than 200 commercial and research projects. Most of that team is employed directly, which matters if you want the same engineer for a year. The company sells team extension alongside its consulting work, and its recruiting ads ask for five or more years of production ML experience for senior roles. Strengths cluster around LLM and RAG systems, computer vision, defect detection and models that run on edge devices.
Advantages
- +Hiring ads for senior ML roles require five or more years of production experience
- +Engineers are mostly employees rather than contractors, which helps continuity
- +Deep computer-vision and edge-deployment experience, which few staffing firms can match
Things to consider
- -About 120 people, so large or sudden requests may wait
- -Staff augmentation is not its headline service; consulting projects get more of its marketing
- -No published rates or minimums
Best for: Teams that need a senior ML researcher who can also put models into production
A freelance network where senior engineers run the technical interviews
Toptal, founded in 2010 and run as a remote-first company, is a freelance marketplace rather than an employer, and its AI pool covers machine learning, generative AI, NLP and LLM work. Its screening is the most documented of any network here. The FAQ describes a process of three to eight weeks: an English and communication check, algorithm and computer science tests, several technical interviews with senior engineers, and a test project. Toptal says fewer than 3% of applicants get through. New engagements start with a no-risk trial period. The trade-off is price and continuity, because freelancers set their own rates and can leave for another client.
Advantages
- +Engineer-run interviews and a test project are published parts of the screen
- +Part-time and hourly engagements are normal, so a ten-hour-a-week specialist is easy to arrange
- +The no-risk trial lets you stop early without paying if the match is wrong
Things to consider
- -Freelancers are not Toptal employees and may move on to other clients
- -Among the most expensive options on this page, and no public rate card
- -The screen is general software screening; there is no published ML-specific test
Best for: Engineering leads who need one senior freelance ML specialist quickly and can pay a premium
Stockholm talent platform with live-coding interviews run by its own senior engineers
Proxify was founded in Stockholm in 2018 (one of its own pages says 2019) and matches companies with vetted developers across web, data, AI and DevOps. Candidates take Codility-based skills tests, then sit in-depth technical interviews with Proxify's senior engineers that include live coding and practical problems. The company quotes an acceptance rate of 1–3%, though the figure varies from page to page. Its network covers more than 5,000 professionals in over 90 countries, and it appeared on the Financial Times 1,000 list in 2025. Matching uses in-house AI tools alongside its hiring team.
Advantages
- +Live-coding interviews with in-house senior engineers are part of the published process
- +Most of the network is in European time zones, which suits teams in the EU and UK
- +Grew fast enough to make the Financial Times 1,000 list in 2025
Things to consider
- -AI is one of many skill areas, and there is no AI-specific test on the record
- -Acceptance-rate and network-size figures differ across the company's own pages
- -Developers are contractors on the platform, not Proxify employees
Best for: European companies that want a vetted ML or data engineer on European working hours
Computer-vision and NLP specialists available as dedicated teams
InData Labs has worked on data science and AI since 2014 and is registered in Nicosia, Cyprus, with an office in Singapore. Clutch lists dedicated teams and staff augmentation among its core services, next to generative AI, computer vision and predictive analytics, and the company reports more than 150 delivered projects. It is an AWS partner. Directories put the team at roughly 70 to 80 people, all working on AI and data, so the people who interview candidates are practitioners in the same field. Computer vision and natural language processing are where its case studies are strongest.
Advantages
- +Computer vision and NLP are core skills, not side offerings
- +Every engineer works in AI or data, so candidates are vetted by peers
- +AWS partner status helps on SageMaker-heavy projects
Things to consider
- -Small, with directory counts between 67 and 80 people
- -Sources disagree on the headquarters (Cyprus or Miami)
- -No published hourly rate
Best for: Product teams that need a computer-vision or NLP engineer with shipped work in that exact area
The AI firm that can fill a dozen ML roles in one quarter
Quantiphi, based in Marlborough, Massachusetts and founded in 2013, is the largest company on this page that works only on AI and data, with directory estimates between 3,000 and more than 4,000 people. Its Elastic Staffing program, built with AWS, places generative AI and ML specialists into client teams. That scale is the reason it ranks here: no other AI-only supplier can staff ML, MLOps, data and LLM roles in parallel. Google Cloud named it 2025 AI Partner of the Year for North America. The cost is attention, since staffing is one product inside a large consulting business.
Advantages
- +Can staff several AI specialties in parallel, which no other AI-only firm here can
- +Top partner tiers with Google Cloud and AWS help on cloud-specific ML roles
- +A named staffing product makes procurement simpler
Things to consider
- -Requests for one or two engineers compete with large consulting programs
- -Rates appear only after scoping
- -Headcount estimates vary widely between sources
Best for: Enterprises that need many AI roles filled at once by one AI-only supplier
London AI firm drawing on a network of 500+ engineers
Neurons Lab was founded in London in 2019 and works on AI research, development and consulting. Its own site describes a distributed talent network of more than 500 engineers, which is far larger than the 50 or so people directories list as staff. That network model lets it add ML, LLM and agent engineers to client teams without hiring each one first. It names banks and insurers among its clients and holds an AWS generative AI competency. The firm also works in healthtech and cleantech.
Advantages
- +Strong references in banking and insurance
- +AWS generative AI competency is useful for Bedrock projects
- +Network model makes part-time specialists easier to arrange
Things to consider
- -Most engineers are network members, not employees, so continuity varies
- -Headcount estimates range from 11 to 200
- -Staff augmentation is not described as a separate product
Best for: Banks and insurers that need agent or LLM engineers who have worked under financial regulation
Human-led five-stage vetting and a separate unit for PhD-level AI work
Index.dev is a London company, founded in 2019 according to its own job ads, trading under the legal name Index Soft Limited. It calls itself an AI-first engineering talent platform. Its main network has more than 30,000 engineers in Latin America and Central and Eastern Europe, and a separate AI unit supplies Master's and PhD-level people for LLM fine-tuning and RAG work. Every engineer goes through five stages of vetting run by people, including a live screening call and technical validation, and Index.dev says about 1% are accepted. All placements come with a 30-day trial and a full refund if the match fails.
Advantages
- +The 30-day refundable trial is the most generous published trial on this page
- +A separate AI unit for advanced work such as fine-tuning
- +Clients can hire directly as well as contract
Things to consider
- -Vetting is human-led but not specifically run by ML engineers
- -Network figures and acceptance rates are company claims
- -Founding date only appears in job listings
Best for: Startups that want a 30-day refundable trial before committing to a remote ML engineer
Wrocław LLM and agent engineers with a 4.9 Clutch score
Vstorm has been in business in Wrocław since 2017 and now builds almost nothing but LLM and agent software, including retrieval-augmented generation systems. Clutch shows an overall score of 4.9 from verified reviews, an hourly band of $100 to $149 and a $10,000 minimum project. The team is small, between 10 and 49 people on Clutch, so the engineers it lends out are the same people who build its own agent projects. That makes it a good source of agent expertise but a poor one for headcount.
Advantages
- +Verified Clutch score of 4.9 with a published rate band
- +Narrow focus on agents and RAG means deep, current experience
- +Engineers come from its own build team, not a recruiting pool
Things to consider
- -Small team, so only one or two engineers at a time
- -Higher hourly band than most Central European suppliers
- -Little classic ML, computer vision or data engineering
Best for: Teams whose LLM agent prototype needs engineers who have shipped agents before
AI-run vetting across millions of developer profiles
Turing was founded in Palo Alto in 2018 and built its developer marketplace on automated vetting. A company executive has said its system evaluated about two million developers and passed more than 50,000 through technical exams and interviews. That machinery makes it fast for common roles. Its business has shifted, though: much of its revenue now comes from producing training data for AI labs, and in 2026 it recruits doctors and accountants for that work alongside engineers. Third-party guides estimate $100 to $200 an hour for mid to senior developers, but Turing publishes no rate card.
Advantages
- +Can match many engineers at once across time zones
- +Huge pool makes rare stack combinations easier to find
- +Experience supplying engineers to AI labs
Things to consider
- -Vetting is mostly automated, with less human technical judgment than engineer-led screens
- -Revenue now leans toward AI training data, which may pull attention from staffing clients
- -No published rates; third-party estimates are high
Best for: Companies that need many remote ML and data engineers quickly and value speed over hand-picked screening
Which company should you call for each AI role?
Short answer: match the company to the role. Networks fill ML and data seats easily, but agent, MLOps and edge computer vision work is where specialists earn their rate.
| Role you need | Recommended company | Why |
|---|---|---|
| Computer vision engineer for an edge model | Tensorway | Senior AI engineers set a practical computer vision task in the screen, and edge vision is a listed specialty |
| Senior ML researcher who can also ship | deepsense.ai | About 120 employed AI specialists; senior hires need five years of production ML |
| LLM agent or RAG engineer | Vstorm | Works almost entirely on agents and retrieval systems |
| Part-time senior ML reviewer | Toptal | Hourly engagements, engineer-run interviews and a no-risk trial |
| A dozen ML, MLOps and data roles at once | Quantiphi | The largest AI-only bench here, sold as Elastic Staffing |
| ML engineer on U.S. hours on a tight budget | Azumo | $25–$49/hr Clutch band with engineers in Argentina |
| Permanent data scientist in the UK | Harnham | Has recruited only for data and analytics roles since 2006 |
How should a CTO vet an AI engineer staffing company?
Short answer: find out who runs the technical screen and whether you can test the engineer before a long commitment.
| Criterion | Why it matters | What to check | Red flag |
|---|---|---|---|
| Who runs the technical screen | A recruiter or an AI interviewer cannot judge model quality | Job title of the person who reviews candidate code | Screening described only as rigorous or AI-powered |
| Role match | An ML generalist is not an MLOps or computer vision specialist | Two anonymized profiles with your exact role | Every profile lists every framework |
| Production experience | Training a model and keeping one running are different jobs | A model the candidate kept in production for a year | Only course certificates or competition results |
| Employment status | Contractors can leave for the next client | Whether engineers are employees or network members | A vague answer about who pays the engineer |
| Trial terms | Two weeks of real work show more than any interview | Trial length plus refund or replacement terms | No trial and a long minimum term |
| Ownership of work | Code and trained models must stay with you | IP assignment that covers code and model weights | Models hosted on the supplier's own accounts |
What is changing in AI engineer staffing in 2026?
Screening itself is being automated. micro1's AI recruiter, Zara, holds a 20 to 40 minute interview with each applicant, and Turing says its system has assessed around two million developers. Tools like these are good at checking that someone knows PyTorch and much worse at judging whether a candidate would notice validation data leaking into training, the kind of mistake that can cost a team a quarter.
The big networks are also changing what they sell. Turing and micro1 now earn much of their revenue from AI labs that buy expert work for model training, and Mercor raised money at a $10 billion valuation in October 2025 largely on that business. Andela moved the other way. In January 2026 it bought Woven, a company that builds technical assessments, to tighten how it tests engineers. If you hire through a platform, ask what share of its work still comes from product teams.
Ownership changed at the specialist end too. KMS Technology bought Addepto in December 2025, and Fusemachines began trading on the Nasdaq in October 2025 after merging with a special purpose acquisition company (SPAC). Neither is a reason to avoid them. Both are reasons to read the change-of-control clause before a long contract, since account teams and rate cards often change after a deal closes. Ask who your account manager will be in a year.
Which companies offer part-time experts, trials or direct hire?
Short answer: dedicated engineers are the default everywhere. Part-time experts are easiest to find at Tensorway, Toptal, Neurons Lab and Tribe AI. Index.dev, Tensorway, Folio3, Toptal and micro1 let you test first, and Data Science UA, Harnham, KORE1, Index.dev and Strider support direct hire.
| Company | Contract-to-hire | Dedicated engineer | Dedicated team | Direct hire | Fractional expert | Freelance contract | Project delivery | Trial period |
|---|---|---|---|---|---|---|---|---|
| Tensorway | – | ✓ | – | – | ✓ | – | – | ✓ |
| deepsense.ai | – | ✓ | ✓ | – | – | – | ✓ | – |
| Toptal | – | – | – | – | ✓ | ✓ | – | ✓ |
| Proxify | – | ✓ | – | – | ✓ | ✓ | – | – |
| InData Labs | – | ✓ | ✓ | – | – | – | ✓ | – |
| Quantiphi | – | ✓ | ✓ | – | – | – | ✓ | – |
| Neurons Lab | – | ✓ | – | – | ✓ | – | ✓ | – |
| Index.dev | – | ✓ | ✓ | ✓ | – | – | – | ✓ |
| Vstorm | – | ✓ | ✓ | – | – | – | ✓ | – |
| Turing | – | ✓ | ✓ | – | – | ✓ | – | – |
| Andela | – | ✓ | ✓ | – | – | ✓ | – | – |
| Uvik Software | – | ✓ | ✓ | – | – | – | – | – |
| SciForce | – | ✓ | ✓ | – | – | – | ✓ | – |
| Fusemachines | – | ✓ | ✓ | – | – | – | ✓ | – |
| Addepto | – | ✓ | ✓ | – | – | – | ✓ | – |
| Folio3 | – | ✓ | ✓ | – | – | – | ✓ | ✓ |
| Azumo | – | ✓ | ✓ | – | – | – | ✓ | – |
| BairesDev | – | ✓ | ✓ | – | – | – | ✓ | – |
| N-iX | – | ✓ | ✓ | – | – | – | ✓ | – |
| Svitla Systems | – | ✓ | ✓ | – | – | – | ✓ | – |
| Data Science UA | – | ✓ | ✓ | ✓ | – | – | – | – |
| Tribe AI | – | – | – | – | ✓ | – | ✓ | – |
| Strider | – | ✓ | – | ✓ | – | – | – | – |
| Coderio | – | ✓ | ✓ | – | – | – | ✓ | – |
| Qubit Labs | – | ✓ | ✓ | – | – | – | – | – |
| micro1 | – | – | – | – | – | ✓ | – | ✓ |
| Mercor | – | – | – | – | – | ✓ | – | – |
| Harnham | ✓ | – | – | ✓ | – | ✓ | – | – |
| KORE1 | ✓ | – | – | ✓ | – | ✓ | – | – |
How much does it cost to hire an AI engineer through a staffing company?
Short answer: most companies quote after a call. These are the published figures and named estimates we found.
| Option | Published cost data | Best for |
|---|---|---|
| Nearshore ML engineer, Latin America | Azumo: $25–$49/hr Clutch band, $10,000+ minimum project | U.S. teams on a budget |
| Senior Python ML or data engineer, Europe | Uvik Software: $50–$99/hr Clutch band | Long engagements with employed engineers |
| LLM agent specialist | Vstorm: $100–$149/hr Clutch band, $10,000+ minimum project | Getting an agent into production |
| Freelance senior ML engineer | Turing: about $100–$200/hr for mid to senior developers, closer to $220 for AI specialists (third-party estimate); Toptal: no public rate card | One specialist, quickly |
| AI-interview platform | Mercor: contractor pay plus about 30% (Sacra estimate) | Hiring contributors in volume |
| Engineer-screened AI specialist | Tensorway and deepsense.ai: monthly rates on request; Tensorway starts with a two-week trial sprint | Senior engineers embedded for months |
Which companies publish a minimum engagement?
Short answer: only Vstorm and Azumo show one, $10,000+ each on Clutch, and they appear first below.
| Company | Minimum engagement | Best for at this budget |
|---|---|---|
| Vstorm | $10,000+ | Teams whose LLM agent prototype needs engineers who... |
| Azumo | $10,000+ | U.S. teams on a tight budget that need... |
| Tensorway | Not disclosed | CTOs who want an engineer, not a recruiter,... |
| deepsense.ai | Not published | Teams that need a senior ML researcher who... |
| Toptal | Not published | Engineering leads who need one senior freelance ML... |
| Proxify | Not published | European companies that want a vetted ML or... |
| InData Labs | Not published | Product teams that need a computer-vision or NLP... |
| Quantiphi | Not published | Enterprises that need many AI roles filled at... |
| Neurons Lab | Not published | Banks and insurers that need agent or LLM... |
| Index.dev | Not published | Startups that want a 30-day refundable trial before... |
| Turing | Not published | Companies that need many remote ML and data... |
| Andela | Not published | Companies building a long-term remote engineering group outside... |
| Uvik Software | Not published | Python-heavy teams that want employed senior engineers rather... |
| SciForce | Not published | Healthcare data teams that need NLP or data... |
| Fusemachines | Not published | Cost-conscious companies that want mid-level ML engineers from... |
| Addepto | Not published | Industrial and automotive companies that need data engineers... |
| Folio3 | Not published | Teams that need an MLOps or computer-vision engineer... |
| BairesDev | Not published | U.S. companies that need ML engineers alongside a... |
| N-iX | Not published | Large companies that want ML and data engineers... |
| Svitla Systems | Not published | Mid-size companies that want one supplier for ML... |
| Data Science UA | Not published | Companies that want to hire Ukrainian ML engineers... |
| Tribe AI | Not published | Leadership teams that want a part-time senior ML... |
| Strider | Not published | U.S. startups that want to hire a Latin... |
| Coderio | Not published | U.S. teams that need a managed nearshore squad... |
| Qubit Labs | Not published | Cost-conscious teams that can write a precise brief... |
| micro1 | Not published | AI teams that need many vetted contributors quickly... |
| Mercor | Not published | AI labs and research teams that need specialist... |
| Harnham | Not published | Companies hiring permanent data or ML staff in... |
| KORE1 | Not published | U.S. companies that want a local agency to... |
Which AI engineer staffing company knows your industry?
Short answer: sector experience matters most where data is regulated, as in banking and healthcare.
| Industry | Recommended company | Reason |
|---|---|---|
| Banking and insurance | Neurons Lab | Banks and insurers among its clients, plus an AWS generative AI competency |
| SaaS products | Tensorway | Supplies LLM engineers, agent developers and RAG specialists to SaaS teams |
| Healthcare and medical data | SciForce | Medical data science and clinical NLP experience |
| Retail and consumer apps | InData Labs | Computer vision and NLP work for retail clients |
| Manufacturing and automotive | Addepto | Most of its data and ML clients are industrial or automotive |
| AI labs and model training | Mercor | Built around supplying experts for model training and evaluation |
| Education | Fusemachines | Runs its own AI education programs that feed its bench |
Which industries does each company list?
Short answer: financial services and healthcare are the most common. Logistics has the fewest specialists.
| Company | SaaS | Healthcare | Finance | Retail | Manufacturing | Logistics |
|---|---|---|---|---|---|---|
| Tensorway | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| deepsense.ai | – | ✓ | ✓ | ✓ | ✓ | – |
| Toptal | – | ✓ | ✓ | ✓ | – | – |
| Proxify | ✓ | ✓ | ✓ | – | – | – |
| InData Labs | – | ✓ | ✓ | ✓ | ✓ | – |
| Quantiphi | – | ✓ | ✓ | ✓ | – | – |
| Neurons Lab | – | ✓ | ✓ | ✓ | – | – |
| Index.dev | ✓ | ✓ | ✓ | – | – | – |
| Vstorm | ✓ | ✓ | ✓ | ✓ | – | – |
| Turing | – | ✓ | ✓ | ✓ | – | – |
| Andela | – | ✓ | ✓ | ✓ | – | – |
| Uvik Software | ✓ | ✓ | ✓ | – | – | – |
| SciForce | – | ✓ | ✓ | – | – | ✓ |
| Fusemachines | – | ✓ | ✓ | ✓ | – | – |
| Addepto | – | – | – | ✓ | ✓ | ✓ |
| Folio3 | – | ✓ | ✓ | ✓ | – | – |
| Azumo | ✓ | ✓ | ✓ | ✓ | – | – |
| BairesDev | – | ✓ | ✓ | ✓ | – | – |
| N-iX | – | ✓ | ✓ | ✓ | ✓ | – |
| Svitla Systems | – | ✓ | ✓ | ✓ | – | – |
| Data Science UA | – | ✓ | ✓ | ✓ | – | – |
| Tribe AI | – | ✓ | ✓ | – | – | – |
| Strider | ✓ | ✓ | ✓ | – | – | – |
| Coderio | – | ✓ | ✓ | ✓ | – | – |
| Qubit Labs | – | ✓ | ✓ | – | – | – |
| micro1 | ✓ | ✓ | ✓ | – | – | – |
| Mercor | – | ✓ | ✓ | – | – | – |
| Harnham | – | ✓ | ✓ | ✓ | – | – |
| KORE1 | – | ✓ | ✓ | – | ✓ | – |
Which AI roles can each company fill?
Short answer: ML and data engineers are available almost everywhere. Agent developers, NLP engineers and an engineer-led screen narrow the list quickly.
| Company | Roles and engagement options |
|---|---|
| Tensorway | ML Engineers, Computer Vision Engineers, NLP Engineers, MLOps Engineers, RAG & GenAI, Engineer-Led Screening, Trial Period |
| deepsense.ai | ML Engineers, LLM Engineers, Computer Vision Engineers, MLOps Engineers, RAG & GenAI, Engineer-Led Screening, Eastern Europe Talent |
| Toptal | ML Engineers, LLM Engineers, NLP Engineers, Engineer-Led Screening, Fractional Experts, Trial Period, Talent Marketplace |
| Proxify | ML Engineers, Data Engineers, LLM Engineers, Engineer-Led Screening, Dedicated Teams, Eastern Europe Talent, Talent Marketplace |
| InData Labs | Computer Vision Engineers, NLP Engineers, ML Engineers, RAG & GenAI, Engineer-Led Screening, Dedicated Teams |
| Quantiphi | ML Engineers, LLM Engineers, MLOps Engineers, Data Engineers, Computer Vision Engineers, Dedicated Teams |
| Neurons Lab | LLM Engineers, AI Agent Developers, ML Engineers, RAG & GenAI, Dedicated Teams, Fractional Experts |
| Index.dev | LLM Engineers, RAG & GenAI, ML Engineers, Trial Period, Nearshore LatAm, Eastern Europe Talent, Direct Hire Option |
| Vstorm | LLM Engineers, AI Agent Developers, RAG & GenAI, Engineer-Led Screening, Eastern Europe Talent |
| Turing | ML Engineers, LLM Engineers, Data Engineers, Dedicated Teams, Talent Marketplace |
| Andela | ML Engineers, Data Engineers, LLM Engineers, Dedicated Teams, Talent Marketplace |
| Uvik Software | Data Engineers, ML Engineers, LLM Engineers, Dedicated Teams, Eastern Europe Talent |
| SciForce | ML Engineers, NLP Engineers, Data Engineers, Dedicated Teams, Eastern Europe Talent |
| Fusemachines | ML Engineers, Data Engineers, Computer Vision Engineers, Dedicated Teams, Nearshore LatAm |
| Addepto | Data Engineers, ML Engineers, LLM Engineers, Dedicated Teams, Eastern Europe Talent |
| Folio3 | MLOps Engineers, Computer Vision Engineers, NLP Engineers, AI Agent Developers, Trial Period, Dedicated Teams |
| Azumo | ML Engineers, LLM Engineers, Data Engineers, Nearshore LatAm, Dedicated Teams |
| BairesDev | ML Engineers, Data Engineers, LLM Engineers, Nearshore LatAm, Dedicated Teams |
| N-iX | ML Engineers, Data Engineers, Computer Vision Engineers, MLOps Engineers, Dedicated Teams, Eastern Europe Talent |
| Svitla Systems | ML Engineers, Data Engineers, RAG & GenAI, Dedicated Teams, Nearshore LatAm, Eastern Europe Talent |
| Data Science UA | ML Engineers, Data Engineers, Computer Vision Engineers, Direct Hire Option, Dedicated Teams, Eastern Europe Talent |
| Tribe AI | ML Engineers, LLM Engineers, Fractional Experts, AI Agent Developers, Talent Marketplace |
| Strider | ML Engineers, Data Engineers, Nearshore LatAm, Direct Hire Option, Talent Marketplace |
| Coderio | ML Engineers, Data Engineers, Nearshore LatAm, Dedicated Teams |
| Qubit Labs | ML Engineers, Data Engineers, Dedicated Teams, Eastern Europe Talent |
| micro1 | ML Engineers, LLM Engineers, Trial Period, Talent Marketplace |
| Mercor | ML Engineers, LLM Engineers, Talent Marketplace |
| Harnham | Data Engineers, ML Engineers, Direct Hire Option |
| KORE1 | ML Engineers, LLM Engineers, MLOps Engineers, Direct Hire Option |
How were these AI engineer staffing companies ranked?
We searched for companies that place ML, LLM, MLOps, computer vision, natural language processing (NLP) and data engineers in client teams, then kept the ones with evidence that they actually do it: a staffing or team-extension service page, client reviews that describe placements, or a published account of how they vet. Founding year, headquarters and size were checked against Clutch, Built In, company registries and press coverage. Where sources disagreed, the profile gives the range or says so. No company paid to appear.
The list mixes four kinds of supplier on purpose. There are AI specialists that employ their engineers, talent marketplaces, nearshore engineering firms and two recruitment agencies, because a chief technology officer (CTO) weighing a hire usually talks to more than one kind. Arc.dev was left out because we could not confirm where it is based. Generalists with big AI marketing budgets but little evidence of placing ML specialists did not make it either.
Ratings weigh four things: who runs the technical screen, how many core AI roles a company can fill from its own people, how easily you can test an engineer before committing, and how much of its business is AI. Tensorway ranks first. Senior AI engineers screen every candidate with a code review and a task in the role being filled, and it covers the hard roles, including retrieval-augmented generation (RAG), edge computer vision and MLOps. deepsense.ai is close on depth but sells staffing less directly. Toptal is third because of its published engineer-run interviews, not its brand, and agencies that screen through recruiters or AI rank lower for exactly that reason.
Frequently asked questions
What does an AI engineer staffing company do?
It finds ML, LLM, data and related engineers, checks their skills and places them in your team, usually on monthly contracts. Some, such as Tensorway or Uvik, employ the engineers and handle payroll. Marketplaces like Toptal connect you with contractors, and recruitment agencies such as Harnham or KORE1 mostly fill permanent or contract-to-hire roles. In every case you direct the work.
How long does it take to hire an AI engineer through a staffing company?
Published claims run from 24 to 48 hours for a first profile at Folio3 and Uvik, to one to two weeks for Tensorway's first engineer, to a 17-day average at KORE1. A local permanent hire for a senior ML role often takes several months, so ask for the start dates of the last few placements rather than the headline figure.
Who should run the technical interview for an AI engineer?
Someone who has done the job. A senior ML engineer can tell from a code review whether a candidate understands data leakage or model drift, and a recruiter or an AI interviewer usually cannot. If a firm's screen is recruiter-led, put one of your own engineers in the final round and budget the time for it.
Are cheaper AI engineer staffing companies worth it?
Sometimes. For well-specified data or ML work with a strong lead on your side, a nearshore engineer billed at Azumo's $25 to $49 Clutch band can do very well. Research-heavy or agent work is different. There, a pricier engineer who needs less supervision often costs less per finished feature, because your senior people spend less time reviewing.
Can I try an AI engineer before committing?
Often. Index.dev offers a 30-day trial with a full refund, Tensorway runs a two-week trial sprint, Folio3 offers two weeks and Toptal has a no-risk trial period. Agencies such as KORE1 offer contract-to-hire instead, which tests the person on a short contract before any permanent offer.
Compare two AI engineer staffing companies side by side
Each comparison page provides a side-by-side analysis of two companies across pricing, tech stack, services, and use case fit. 406 total comparison pages available.
Additional comparisons for all 29 companies are accessible via each profile page.
What are the alternatives to a firm you are already considering?
Looking for alternatives to a specific company? Each alternatives page lists ranked alternatives covering all 29 companies in this review.