Python Machine Learning Engineer
Turing • Remote, United States, Bangladesh, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, Ghana
Education
Bachelor's
Type
Hourly
Listed
186d ago
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- Weekly hours
- 10 hrs/week
- Timezone overlap
- Partial overlap with US Pacific time required
- Contract length
- 4 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’re looking for a ML Developer to drive the design, development, and delivery of advanced machine learning solutions. The ideal candidate is not just a strong individual contributor but also a technical leader capable of setting direction, mentoring team members, and ensuring that ML initiatives align with business goals. Competitive ML experience (e.g., Kaggle, benchmarks) is a strong plus.
What does day-to-day look like
- Own end-to-end DS/ML solution development — from data pipelines and model design to deployment and monitoring.
- Translate business objectives into robust ML architectures that accurately capture business logic and context.
- Collaborate cross-functionally with Product, Engineering, and Business stakeholders to define problem statements and success metrics.
- Evaluate and optimize models for performance, scalability, and accuracy using state-of-the-art techniques.
- Stay current with advancements in AI/ML research and apply relevant innovations to improve outcomes
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Statistics, or a related quantitative field.
- 4+ years of hands-on DS/ML development experience,
- Proficiency in key DS/ML areas and frameworks:Supervised and Unsupervised Learning Time-Series Forecasting Natural Language Processing (NLP) Computer Vision (CV) Statistical Modeling and Inference
- Expertise in Python and core libraries (Pandas, NumPy, Scikit-learn, etc.).
- Ability to understand and apply different models to real-world use cases
- Strong understanding of data preprocessing, feature engineering, model tuning, and evaluation metrics.
- Proven ability to design scalable, production-grade ML systems.
Preferred Qualifications
- Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
- Experience with cloud data platforms (Databricks, AWS, etc.)
- Hands-on experience with PySpark and Databricks Platform
- Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
Bonus
- Experience and knowledge in Kaggle competitions and Benchmarks, such as MLEBench
- Experimenting with new technologies and frameworks based on Research papers published in top conferences and journals
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. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)
- Employment type : Contractor assignment (no medical/paid leave)
- Duration of contract : 3 month; [expected start date is next week]
- Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico
Evaluation Process (approximately 75 mins)
- Two rounds of interviews as follows:Interview 1: Technical, 60 mins Interview 2: Onboarding & cultural discussion, 15 mins
Requirements
- Critical Thinking
- Must be eligible to work in one of: Remote, United States
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a Machine Learning Engineer role, written in-house to help you prepare.
How do you choose between a simpler interpretable model and a more complex model that performs marginally better?
The decision depends on how the model's output is used downstream. If a human needs to act on and justify individual predictions, like in lending or healthcare, interpretability often outweighs a small accuracy gain. If the model feeds an automated system where explainability isn't a hard requirement, I'll take the complexity if the performance gain is meaningful and validated, not just noise.
Explain how you would set up a proper train, validation, and test split for a time series problem.
Random splitting leaks future information into training for time series, so I split chronologically instead, training on the earliest period, validating on the next, and testing on the most recent. Any cross-validation also needs to respect time order, using something like rolling-origin validation, rather than standard k-fold, which would otherwise let the model see the future during validation.
What statistical test would you use to determine if an A/B test result is significant, and what assumptions does it rely on?
For a conversion-rate comparison, a two-proportion z-test or chi-squared test is standard, and it assumes independent observations and a large enough sample size for the normal approximation to hold. If the sample is small or the metric isn't binary, I'd switch to a more appropriate test, since applying the wrong test's assumptions is a common source of false confidence in A/B results.
How do you approach hyperparameter tuning efficiently when the model is expensive to train?
I use a coarse random search first to identify the promising region of the hyperparameter space, since grid search wastes compute on combinations unlikely to matter. From there, Bayesian optimization narrows in on the best configuration with far fewer expensive training runs than an exhaustive search would require, which matters a lot when each run is costly.
This listing calls for this tool directly. Prep for the technical screen:
What to Expect
Looking at Turing Software Engineering listings we've tracked, contracts in this domain typically run about 8.4 weeks. Actual length varies by project, but this gives you a realistic baseline going in. This listing's 4-week contract is shorter than the typical 8.4-week Turing Software Engineering engagement.
Based on 28 extracted Turing Software Engineering listings.
Why this role
This Python Machine Learning Engineer role covers building and evaluating Python-based ML engineering tasks used to test AI models on real machine learning pipeline problems. Grading depends on knowing common Python ML libraries well enough to catch a subtly wrong implementation.
Skills and categories
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Common 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.
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 Software Engineering work look like for a Python Machine Learning Engineer?
Tasks here are scoped to Software Engineering, not generic labeling. As a Python Machine Learning Engineer, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Critical Thinking, Coding, and Python are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How many hours per week does this role require?
Based on the listing, this role is scoped at about 10 hours per week, over roughly a 4-week contract. Treat this as a real commitment expectation, not a loose estimate.
How much does this specific role pay?
The listing doesn't state a rate. The $12–$30/hr shown here is our estimate from the role type and location (see /pay-methodology), so treat it as a rough guide and confirm the actual rate with the platform before committing time.
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 the United States, Bangladesh, Egypt and 7 other countries?
This specific role is open only to people based in the United States, Bangladesh, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, and Ghana. If you are somewhere else, applying is unlikely to lead to an offer even if you pass the assessment, because the restriction is usually about where the work can legally be contracted rather than your skills. Read the full description for any tax-residency or right-to-work caveats before you apply, since they can differ by country.