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.

Perks of Freelancing With Turing

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

Duration of Contract: 3 months (adjustable based on engagement).

• 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.

• Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused).

Technical Interview with live coding challege (60 mins).

Work arrangement: Fully remote

Applicant eligibility: 10 eligible countries

Engagement Type: Contractor assignment (no medical/paid leave).