Machine Learning Engineer
$130k - $200k • Remote • Full-time
Posted 4mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Remote
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
10a Labs is seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems for AI safety and model evaluation applications. This role blends strong ML engineering with an experimental approach, tackling problems in reinforcement learning, model evaluations, language models, and multimodal systems. You will transform ambiguous technical questions into rigorous experiments and scalable systems, collaborating with a diverse team of engineers, analysts, and subject-matter experts to support leading AI organizations.
Responsibilities
- Design and execute ML experiments to assess the capabilities, behavior, robustness, and limitations of advanced AI systems.
- Develop and evaluate models across reinforcement learning, NLP/LLMs, computer vision, and multimodal ML.
- Build evaluation pipelines, benchmarks, datasets, and metrics for frontier AI systems.
- Train, fine-tune, and evaluate models for safety, security, and other high-impact applications.
- Develop reliable tooling and infrastructure for running ML experiments and evaluations at scale.
- Analyze experimental results, identify model failure modes, and translate findings into new experiments and technical approaches.
Requirements
- 3-5+ years of experience in machine learning, research engineering, or a related technical field.
- Strong Python skills and experience with ML frameworks like 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, Model Context Protocol, agent benchmarks, and security risks to AI agents.
- Experience in reinforcement learning, NLP/LLMs, computer vision, or multimodal ML.
- Strong software engineering fundamentals and the ability to work independently on ambiguous technical problems.
- Experience with RLHF/RLAIF, reward modeling, policy optimization, or other model post-training techniques (nice to have).
- Experience evaluating frontier language or multimodal models (nice to have).
- Experience with adversarial evaluations, robustness testing, or AI safety (nice to have).
- Experience with distributed training, cloud ML infrastructure, or large-scale ML systems (nice to have).
Benefits
- Salary Range: $130K–$200K, depending on experience and location
- Performance-based annual bonus
- Support for conferences, continuing education, or leadership training
- Comprehensive health, dental, and vision coverage
- Generous PTO and paid holiday schedule