Machine Learning Expert

This is a fully remote position, open to applicants in United States.

📋 Description

• Generate innovative concepts for challenging machine learning engineering tasks within a long-term AI research initiative at a prominent AI laboratory.

• Design tasks that are sufficiently difficult so that cutting-edge models can only solve them in a maximum of 2 out of 8 attempts.

• Concentrate mainly on inference, evaluation, and systems work rather than extensive model training.

• Develop a well-balanced variety of tasks that utilize both GPU and CPU-only resources.

• Clearly articulate the reasons each problem poses challenges for a cutting-edge model.

• Primarily focus on contributing ideas; the construction or review of tasks is not a requirement.

⛳️ Requirements

• Currently holds or has recently held a position as an ML research engineer, research scientist, or applied scientist.

• Practical experience in personally training, fine-tuning, or optimizing models using PyTorch or JAX.

• Extensive knowledge in at least one area: LLM pretraining, alignment, or evaluations; GPU inference and performance, including vLLM, Triton, CUDA, or profiling; reinforcement learning; or scientific ML in weather and climate, physics, or biology.

• Capable of articulating why a problem is challenging for a cutting-edge model.

• Experience in writing benchmark or evaluation questions is advantageous.

• A PhD in ML, CS, or physics, or an MSc accompanied by substantial research output is a plus.

• Having publications is beneficial.

• Prior contracts with Mercor showcasing strong performance are a plus.

• Candidates must not be on an H1-B or STEM OPT visa, as Mercor is unable to support these applicants.

• Software or full-stack engineers whose AI expertise is primarily in LangChain or RAG applications are not suitable for this role.

• Backgrounds that consist solely of AI trainer, rater, or annotator roles are not appropriate.

🏝️ Benefits

• Fully remote position.

• Flexible scheduling.

• Weekly payments through Stripe or Wise based on services rendered.

• Project durations may be extended, shortened, or concluded early based on needs and performance.

• Competitive compensation.

• Collaboration with leading researchers in the field.

• Opportunity to contribute to the evolution of next-generation AI systems.

• Up to $800 for each successful referral, subject to referral limits.

• Reasonable accommodations available upon request.