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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning research with a focus on inference, evaluation, and systems work. Proficient in generating challenging tasks for frontier models and possesses deep knowledge in areas such as LLM pretraining, GPU inference, and scientific ML.
Highest-signal resume keywords
Machine Learning Research EngineerHands-On Experience With PyTorchDeep Knowledge Of LLM PretrainingGPU Inference And PerformancePhD In ML, CS, Or Physics
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Model TrainingFine-Tuning ModelsOptimizing ModelsBenchmark WritingEvaluation Questions
Soft Skills
Problem Explanation
Tools & Technologies
JAXVLLMTritonCUDAProfiling
Industry Keywords
AI ResearchFrontier ModelsReinforcement LearningScientific MLClimate Modeling
Tech Stack
Tools & technologiesPyTorch
About the role
Key responsibilities & impact- Generate ideas for difficult machine learning engineering tasks for a long-horizon AI research project with a leading AI lab
- Design tasks challenging enough that frontier models solve them in no more than 2 of 8 attempts
- Focus primarily on inference, evaluation, and systems work rather than heavy model training
- Develop a roughly balanced mix of GPU and CPU-only tasks
- Clearly explain why each problem is difficult for a frontier model
- Contribute primarily ideas; building or reviewing the tasks is not required
Requirements
What you’ll need- Current or recent role as an ML research engineer, research scientist, or applied scientist
- Hands-on experience personally training, fine-tuning, or optimizing models in PyTorch or JAX
- Deep knowledge of 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
- Able to explain why a problem is hard for a frontier model
- Experience writing benchmark or evaluation questions is a plus
- PhD in ML, CS, or physics, or an MSc plus strong research output is a plus
- Publications are a plus
- Prior Mercor contracts with strong performance are a plus
- Must not be an H1-B or STEM OPT candidate, as Mercor cannot support these candidates
- Software or full-stack engineers whose AI experience is mainly LangChain or RAG applications are not a fit
- Backgrounds limited to AI trainer, rater, or annotator work are not a fit
Benefits
Comp & perks- Fully remote role
- Flexible own schedule
- Weekly payments via Stripe or Wise based on services rendered
- Projects may be extended, shortened, or concluded early depending on needs and performance
- Competitive pay
- Collaboration with leading researchers
- Opportunity to help shape the next generation of AI systems
- Up to $800 for each successful referral, subject to referral limits
- Reasonable accommodations upon request