Machine Learning Engineer for AI Benchmarking

Role Overview

Join a dynamic team as a Machine Learning Engineer (MLE Bench), where you will play a pivotal role in benchmark-driven evaluation projects focused on real-world machine learning systems. This position offers the opportunity to work hands-on with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows, all aimed at assessing and enhancing the capabilities of advanced AI systems. The ideal candidate will bridge the gap between research and engineering, engaging deeply with models, data, and infrastructure in realistic ML environments.

Key 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, 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.

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.

Work Terms

• Commitments Required: At least 4 hours per day and a minimum of 20 hours per week with 4 hours of overlap with PST.
• Engagement Type: Contractor assignment (no medical/paid leave).
• Duration of Contract: 3 months (adjustable based on engagement).
• Location: Open to candidates from India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, Mexico.

Compensation

Compensation details will be discussed during the interview process.

Eligibility

This position is open to candidates who meet the qualifications and are located in the specified countries.

Perks of Freelancing

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