Remote ML Engineer

You are being offered a position as a Machine Learning Engineer (MLE Bench) at Turing, a leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. In this role, you will contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

• *Role Overview:**

As a Machine Learning Engineer at Turing, your day-to-day responsibilities will include:

• Working with real-world ML codebases to support MLE Benchstyle evaluation tasks.
• Building, running, and modifying model training, evaluation, and inference pipelines.
• Preparing datasets, features, and metrics for ML benchmarking and validation.
• Debugging, refactoring, and improving production-like ML systems for correctness and performance.
• Evaluating model behavior, failure modes, and edge cases relevant to benchmark tasks.
• Writing clean, reproducible, and well-documented Python code for ML workflows.
• Participating in code reviews to ensure high standards of engineering quality.
• Collaborating with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.
• *Qualifications Required:**

To be considered for this role, you must meet the following qualifications:

• 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.

Turing also offers some perks for freelancers, including:

• Working in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.

If you are excited about the opportunity to work on challenging AI projects and meet the qualifications mentioned above, we encourage you to apply for the position. You are being offered a position as a Machine Learning Engineer (MLE Bench) at Turing, a leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. In this role, you will contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

• *Role Overview:**

As a Machine Learning Engineer at Turing, your day-to-day responsibilities will include:

• Working with real-world ML codebases to support MLE Benchstyle evaluation tasks.
• Building, running, and modifying model training, evaluation, and inference pipelines.
• Preparing datasets, features, and metrics for ML benchmarking and validation.
• Debugging, refactoring, and improving production-like ML systems for correctness and performance.
• Evaluating model behavior, failure modes, and edge cases relevant to benchmark tasks.
• Writing clean, reproducible, and well-documented Python code for ML workflows.
• Participating in code reviews to ensure high standards of engineering quality.
• Collaborating with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.
• *Qualifications Required:**

To be considered for this role, you must meet the following qualifications:

• 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.

Turing also offers some perks for freelancers, including:

• Working in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.

If you are excited about the opportunity to work on challenging AI projects and meet the qualifications mentioned above, we encourage you to apply for the position.