Remote ML Engineer

Turing; Turkey; Remote; TRY 4,129,000 - 6,193,000; Part time

Benefits offered by this job

Fully remote

3-month contract

4+ hrs/day, 20 hrs/week overlap with 4

Job summary

Turing seeks an experienced Machine Learning Engineer to contribute to benchmark-driven evaluation projects on real-world ML systems. You will work with production-grade ML code, training and evaluation pipelines, and deployment-oriented tasks to help assess advanced AI systems.

The ideal candidate has 3+ years in ML/Software, strong Python, and experience with PyTorch, TensorFlow or JAX. This is a contractor role for 3 months with at least 4 hours daily and 20 hours weekly overlap with PST.

Qualifications

• 3+ years of experience as ML/Software Engineer (ML-focused).
• Proficient in Python for ML workflows.
• Hands-on experience with training, evaluation, and inference pipelines.
• Experience with ML frameworks (PyTorch, TensorFlow, JAX).
• Strong debugging and problem-solving skills.
• Excellent spoken and written English communication.

Responsibilities

• 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 Python code for ML workflows and participate in code reviews.
• Collaborate with researchers and engineers to design challenging ML tasks for AI system evaluation.

Skills

Python for ML

ML pipelines

Code debugging

English communication

Tools

PyTorch

TensorFlow

JAX

Job description

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.
• 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)

Evaluation Process:

• Technical Interview with live coding challege (60 mins)