Remote ML Engineer - 60735

Turing; Gurugram District; Remote; INR 1,200,000 - 1,800,000; Part time

Benefits offered by this job

Fully remote environment

Opportunity to work on cutting-edge AI projects

Flexible hours with minimum 20 hours a week commitment

Job summary

A leading AI research accelerator is seeking experienced Machine Learning Engineers to contribute to benchmark-driven evaluation projects. You will work with production-grade ML codebases, build evaluation pipelines, and collaborate on real-world tasks. Ideal candidates should have at least 3 years of experience, strong Python skills, and a solid understanding of machine learning fundamentals. This is a contractor assignment requiring a minimum commitment of 20 hours per week, fully remote and based in India.

Qualifications

• Minimum 3+ years as a Machine Learning Engineer or Software Engineer focused on ML.
• Strong understanding of machine learning fundamentals.
• Experience with model training, evaluation, and inference pipelines.

Responsibilities

• Work with real-world ML codebases for evaluation tasks.
• Build and modify ML training, evaluation, and inference pipelines.
• Debug and improve production-like ML systems.

Skills

Proficiency in Python

Strong problem-solving skills

Excellent communication skills

Tools

PyTorch

TensorFlow

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)