How do you vet ML engineers?

Profile and portfolio review, a practical technical assessment, a live ML and system design interview with a senior engineer, and communication and reference checks.

What share of applicants pass?

Only a small fraction of applicants reach our network. Exact figures vary by specialty and period, and we are happy to share current numbers on a call.

Can I interview the engineers myself?

Of course. You meet every shortlisted engineer and make the final decision.

What if the engineer is not a good fit?

We replace them, typically within two weeks, and cover the handover so you do not lose momentum.

Do you verify experience and references?

Yes. We check past roles and speak to references before an engineer joins our network.

How do remote engineers work with my team?

In your tools: your chat, your repositories and your project tracker. They join standups and demos like any other team member.

What about time zone overlap?

We match on overlap as well as skills. You can choose engineers whose working hours share three, four or more hours with yours, and the planner above shows how it works.

How is English and communication handled?

Written and spoken English is assessed during vetting. Engineers are expected to communicate clearly in async channels as well as on calls.

How do I manage performance?

You set goals and review work as you would for employees. We run regular check-ins with both sides and step in if anything slips.

Can the engineer work from my office or hours?

Where it makes sense we can agree on-site days, core hours or on-call windows, depending on location and local rules.

Who owns the code and models?

You do. IP assignment is in the contract, and work is delivered into your repositories and cloud accounts.

How is my data protected?

Engineers sign confidentiality agreements and work in your environment through least-privilege, logged access. Data stays where you put it.

Can engineers work on secured devices or VDI?

Yes. We can follow your device, VPN or virtual desktop requirements.

Do you support compliance requirements?

We work with your compliance team on regulated use cases and align with your policies. Specific certifications depend on your requirements.

What happens when an engagement ends?

Access is revoked, assets are returned or deleted, and documentation and handover notes are delivered.

How is pricing structured?

A monthly rate per engineer based on seniority and specialty, with no recruiting fee. You receive a clear quote with the shortlist.

How fast can an engineer start?

Most start within one to two weeks of selection, depending on availability and notice.

Is there a minimum commitment?

Full-time engagements typically begin with three months, with flexible notice afterwards. Part-time and project options have shorter terms.

Can I convert an engineer to my own employee?

Yes, under contract-to-hire terms we agree in advance.

It depends on your local market and the engineer's location. The calculator above gives an illustrative estimate, and we can prepare a precise comparison for your case.

Hire Remote ML Engineers

Hire remote ML engineers who ship

Pre-vetted machine learning engineers from the top few percent, matched to your stack and your time zone. Meet a shortlist in 48 hours and start within a couple of weeks.

Top 3% vetted
Time-zone matched
2-week replacement

Get my shortlist Check time overlap

Match finderML engineer · UTC±3

Aarav K.

Senior ML Engineer

Bengaluru · 8 yrs experience

96%match

LLMs and RAG

PyTorchRAGLangChainvLLM

Available in 5 daysVetted

Time-zone overlap3.5h shared with your team

0h6h12h18h24h

Your team, ParisAarav, Bengaluru

Shortlist in

48 hours

Vetting

Top 3% accepted

How we vet

Only about three in a hundred make it through

Five stages, run by senior ML practitioners. Hover a stage to see what is tested. Figures are illustrative of our typical funnel.

Stage 1 of 5

Applicants

Engineers apply or are sourced from our network and referrals.

Role and seniority fit
Location and availability
Compensation expectations

Starting pool

Skills

The periodic table of ML talent

Thirty-six skills our engineers are tested on. Filter a family, hover a tile for details.

Frameworks

PyTorch

Research and production deep learning, from training loops to serving.

Time zones

See exactly how your working day lines up

Pick where your team sits. Bars show a standard 9 to 5 day for each hub, on your clock. Real schedules are flexible.

Your team is in

03691215182124

Latin AmericaBuenos Aires · UTC-3

4hGood

Eastern EuropeWarsaw · UTC+1

8hGreat

AfricaLagos · UTC+1

8hGreat

IndiaBengaluru · UTC+5.5

3.5hLimited

Southeast AsiaHo Chi Minh City · UTC+7

2hLimited

Your 9 to 5Engineer 9 to 5Shared hours

Sample profiles

What a vetted engineer looks like on paper

Illustrative, anonymised profiles. Hover or tap a card to see the assessment scores behind it.

Staff ML Engineer

Recommendation systems

11 yrsVetted

Hover to flip

Assessment

Coding94
ML fundamentals96
System design91
Communication88

Led ranking rebuilds serving tens of millions of requests a day. Strong on offline-to-online metric gaps.

Senior GenAI Engineer

Agents and evaluation

7 yrsVetted

Hover to flip

Assessment

Coding90
ML fundamentals89
System design93
Communication95

Built evaluation harnesses and guardrails for production assistants. Clear writer, great in design reviews.

ML Engineer

Forecasting and time series

6 yrsVetted

Hover to flip

Assessment

Coding92
ML fundamentals94
System design85
Communication90

Shipped demand forecasting for retail and logistics. Excellent statistical judgment and documentation.

Savings estimator

Estimate what a remote team could save you

Enter your own local cost. Percentages are illustrative ranges, not quotes. Your actual rate depends on seniority and specialty.

Engineers to hire3Local cost per engineer / year$180k

Where they would be based

Local cost means fully loaded: salary, benefits, taxes, equipment and recruiting.

Estimated yearly saving$205,20038% lower than local hiring

Local hires$540,000

Remote via Aarvexa$334,800

No recruiting fees
First profiles in 48 hours
Start in about 2 weeks, not 10

First 30 days

From signed to shipping in four weeks

A clear ramp so your new engineer is productive fast.

Week 1Plug in

Week 1

Plug in

Access, repositories and environments set up
Security and NDA steps completed
Meet the team and agree communication rhythm
First small pull request merged

Week 2Own a slice

Week 2

Own a slice

A scoped problem with clear success metrics
Baseline model or pipeline running
First demo to your stakeholders
Written plan for the next sprint

Week 3Ship to staging

Week 3

Ship to staging

Evaluation suite and monitoring in place
Code and model review with your engineers
Documentation and runbook drafted
Integration tested end to end

Week 4Go live

Week 4

Go live

Release behind a feature flag
Dashboards and alerts handed over
Retro and roadmap for month two
Success metrics reviewed with you

Engagement models

Pick the way of working that fits

Start with a model, change it later. Terms below are typical and set out in your agreement.

Part-time

Most popularFull-time dedicated

Project squad

Contract-to-hire

Best for

Advisory, audits and short builds

Core product and platform work

A defined deliverable with a deadline

Evaluating before you hire directly

Commitment

10 to 20 hours a week

40 hours a week

Team sized to scope

40 hours a week

Typical start

About 1 week

About 1 to 2 weeks

About 2 weeks

Minimum term

1 month

3 months

Per project

3 to 6 months

Replacement

Within 2 weeks

Within the squad

Within 2 weeks

Flexibility

Easy to increase hours

Add or release with 30 days' notice

Scope-based changes

Convert on agreed terms

FAQ

Frequently Asked Questions

Straight answers on hiring remote ML engineers: vetting, time zones, security, cost and timelines.

You get a pre-vetted machine learning engineer who works full-time or part-time for you, from their own location, as an extension of your team. We handle sourcing, vetting, contracts and payroll logistics. You direct the work.

GenAI and LLM engineers, general ML engineers, computer vision, NLP, recommendation systems, time series and forecasting, speech, edge ML, MLOps and data engineers.

Every engineer is screened by senior ML practitioners before you ever see a profile, and we stay involved after the start with replacement, performance check-ins and contract management.

Yes. Many clients start with one engineer and add more once the first is productive.

Book a free consultation, share the role you need, and we send a shortlist of matched profiles, usually within 48 hours.

Shortlist clock

Meet your ML engineers in 48 hours

48Hours

00Minutes

00Seconds

Tell us the role, stack and time zone. We send two to four matched, vetted profiles with rates and availability, free and with no obligation.

Get my shortlist Estimate savings