Machine Learning Expert (Remote |

Synthires; Alaska; À distance; USD 207 000 - 276 000; Temps partiel

Avantages offerts par ce poste

Remote work

Résumé du poste

Synthires is seeking an experienced Machine Learning Expert for a remote, hourly contract to contribute high-impact ML engineering task ideas for a long-horizon AI research project with a leading AI lab.

The role emphasizes designing problems that push frontier models in inference, evaluation, and systems engineering, with responsibilities spanning GPU and CPU workloads and clear explanations of why challenges arise.

Qualifications

• Current or recent experience as an ML research engineer, research scientist, or applied scientist.
• Hands-on experience training, fine-tuning, or optimizing models using PyTorch or JAX.
• Deep knowledge of LLMs, GPU inference, RL, or scientific ML.

Responsabilités

• Develop ideas for challenging machine learning engineering tasks for an AI research project.
• Design problems that are difficult for frontier models to solve consistently.
• Focus on inference, evaluation and systems engineering with GPU/CPU workloads.
• Explain clearly why each proposed problem is challenging for advanced AI models.
• Contribute task concepts without needing to build or review the tasks themselves.

Connaissances

ML research experience

PyTorch

JAX

LLMs

GPU inference

Reinforcement learning

Scientific ML

Formation

PhD in ML / CS / Physics

Outils

PyTorch

JAX

Description du poste

Machine Learning Expert (Remote | $150–$200/hr)

Description:

Machine Learning Expert (Remote | $150–$200/hr)

Position: Machine Learning Expert

Type: Hourly Contract

Compensation: $150–$200 per hour

Location: Remote

About the Opportunity

This opportunity is for experienced machine learning research engineers, research scientists, and applied scientists to contribute challenging machine learning engineering task ideas for a long-horizon AI research project with a leading AI lab. The focus is on designing problems that test the limits of frontier AI models, particularly in inference, evaluation, and systems engineering.

Key Responsibilities

• Develop ideas for challenging machine learning engineering tasks for an AI research project.
• Design problems that are difficult for frontier models to solve consistently.
• Focus on inference, evaluation, and systems engineering, with tasks involving both GPU and CPU workloads.
• Explain clearly why each proposed problem is challenging for advanced AI models.
• Contribute task concepts without needing to build or review the tasks themselves.

Required Qualifications

• Current or recent experience as an ML research engineer, research scientist, or applied scientist.
• Hands-on experience personally training, fine-tuning, or optimizing models using PyTorch or JAX.
• Deep knowledge of at least one of the following areas:
• Large language models (LLMs), including pretraining, alignment, and evaluations.
• GPU inference and performance, including vLLM, Triton, CUDA, or profiling.
• Reinforcement learning (RL).
• Scientific machine learning, including weather, climate, physics, or biology.
• Ability to explain why specific machine learning problems are difficult for frontier models.

Preferred Qualifications

• Experience developing benchmark or evaluation questions.
• PhD in machine learning, computer science, or physics, or an MSc with strong research output.
• Relevant research publications.
• Previous Mercor contract experience with strong performance.

Compensation

• $150–$200 per hour.
• Remote hourly contract engagement.