MLE Bench – ML Engineers
Turing • Bangladesh, Brazil, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, Ghana
Education
Any
Type
hourly
Pay Rate (by country)
$12–$30/hr
Listed
13d ago
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Turing: our referral track record
We've referred 677 candidates to Turing roles. 2% (15) were placed.
Turing: typical time to hire
Based on 15 tracked placements across all Turing roles on our site.
What We Know About This Role
- Interview
- Required i As stated in the listing: “Duration of Contract: 3 months”
- Weekly hours
- 20 hrs/week
- Timezone overlap
- Partial overlap with US Pacific time required
- Contract length
- 12 weeks
About this Role
From the Turing listing
About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L
Role Overview
We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems.
The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.
What does day-to-day life look like?
Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.
Requirements
Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.
Perks of Freelancing With Turing
Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.
Offer Details
Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement) Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, Mexico
Evaluation Process
Technical Interview with live coding challege (60 mins)
Requirements
- Machine Learning
- Python
- Must be eligible to work in one of: Bangladesh, Brazil
What to Expect
Looking at Turing STEM listings we've tracked, contracts in this domain typically run about 9.2 weeks. Actual length varies by project, but this gives you a realistic baseline going in. This listing's 12-week contract is longer than the typical 9.2-week Turing STEM engagement.
Based on 19 extracted Turing STEM listings.
Eligible Languages
Fluent proficiency in English
Why This Role
As a MLE Bench – ML Engineers, you don't need prior AI experience to start, just solid STEM knowledge. The rate ($21/hr) and remote setup make it an accessible way into the AI training industry.
Skills & Categories
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Frequently Asked Questions
Do I need to be a software engineer to work for Turing?
No, not anymore. Turing built its name matching senior engineers with Silicon Valley companies, but it has since expanded into AGI infrastructure work and now hires non-engineering domain experts, technical writers, and researchers for post-training data annotation and RLHF. A strong analytical background and excellent English matter more than coding ability.
How does Turing's talent matching work?
Turing calls it the Intelligent Talent Cloud. You build a profile and go through vetting (automated tests, an AI-powered interview, practical skill assessments), and once vetted, Turing's algorithm surfaces your profile directly to partner companies like Fortune 500s and top AI labs. You don't browse listings or bid on work; matches come to you.
How and when does Turing pay contractors?
Monthly, in USD, via Deel, Payoneer, or direct bank transfer. You're engaged as an independent contractor responsible for your own local taxes. Plan your cash flow around a monthly cycle if you're used to weekly payouts elsewhere.
What does task-based AI training work actually look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does STEM work look like for a MLE Bench – ML Engineers?
Tasks here are scoped to STEM, not generic labeling. As a MLE Bench – ML Engineers, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to STEM) rather than following a one-size-fits-all rubric. If you don't have hands-on STEM background, this is likely not the right listing to start with.
How many hours per week does this role require?
Based on the listing, this role is scoped at about 20 hours per week, over roughly a 12-week contract. Treat this as a real commitment expectation, not a loose estimate.
Do I need to be fluent in English?
Yes. This role specifically requires English proficiency. You will likely be evaluated on written fluency during the assessment, not just conversational level. If English is not your first language or you are not professionally fluent, this is not the right role. Filter for your native language to find better-matched listings.
What happens when I click Apply on this listing?
You'll be taken to Turing's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Can I apply from outside Bangladesh, Brazil, Egypt and 7 other countries?
This specific role is restricted to Bangladesh, Brazil, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, Ghana. If you are outside these locations, applying is unlikely to result in an offer even if you pass the assessment. Check the full job description for any VPN or tax-residency caveats.
Is there an interview?
Yes. Technical Interview with live coding challege (60 mins)