Remote AI Safety ML Engineer — Experiments & Evaluation

10a Labs; United States; On-site; USD 130,000 - 200,000; Full time

Benefits offered by this job

Fully remote (US-based)

Health benefits

Generous PTO

Professional Development

Conference support

Job summary

10a Labs is seeking a Machine Learning Engineer to design, build, and evaluate advanced ML systems focused on AI safety and model evaluation. The role emphasizes experiments, scalable tooling, and rigorous analysis.

You'll work with engineers, analysts, red teamers, and subject-matter experts to push frontier AI capabilities while ensuring robust, secure deployments in a fully remote US-based environment. Candidates should pair strong ML fundamentals with the ability to turn ambiguous questions

Qualifications

• 3–5 years of experience in machine learning, research engineering, or a related technical field.
• Strong Python skills and experience with ML frameworks such as PyTorch or JAX.
• Hands-on experience training, fine-tuning, or evaluating modern ML models.
• Strong understanding of experimental design, model evaluation, and quantitative analysis.
• Familiarity with agentic AI fundamentals, including common harnesses and security risks to AI agents.
• Experience in one or more of the following: reinforcement learning, NLP/LLMs, computer vision, or multimodal ML.

Responsibilities

• Design and run ML experiments to evaluate AI systems' capabilities and robustness.
• Develop and evaluate models across RL, NLP/LLMs, CV, and multimodal ML.
• Build evaluation pipelines, benchmarks, datasets, and metrics.
• Train, fine-tune, and evaluate models for safety and security.
• Develop scalable tooling and infrastructure for ML experiments.
• Analyze results and translate findings into new experiments.

Skills

Python

PyTorch/JAX

ML Experimentation

Experimental Design

Agentic AI

Reinforcement Learning

NLP/LLMs

Tools

PyTorch

JAX

Job description

10a Labs is seeking a Machine Learning Engineer to design, build, and evaluate advanced ML systems focused on AI safety and model evaluation. The role emphasizes experiments, scalable tooling, and rigorous analysis.

You'll work with engineers, analysts, red teamers, and subject-matter experts to push frontier AI capabilities while ensuring robust, secure deployments in a fully remote US-based environment. Candidates should pair strong ML fundamentals with the ability to turn ambiguous questions