About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.
Location & Travel Expectations
We are primarily seeking candidates based in the Washington, DC, New York City, San Francisco Bay Area, and Denver metropolitan areas. Candidates hired in these locations will be expected to work from a 10a Labs office at least two days per week.
All new hires will participate in in-person onboarding in Washington, DC, New York City, or San Francisco during their first week. Occasional travel may also be required for interviews, in-person meetings, and other business needs.
We are seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems across AI safety and model evaluation applications.
This role combines strong ML engineering with an experimental mindset. You will work on problems involving reinforcement learning, model evaluations, language models, multimodal systems, and classifiers, taking ambiguous technical questions and turning them into rigorous experiments and scalable systems.
You will collaborate closely with engineers, analysts, red teamers, and subject-matter experts supporting leading AI organizations.
What You'll Do- Design and run ML experiments to evaluate 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 to run ML experiments and evaluations at scale.
- Analyze results, identify model failure modes, and translate findings into new experiments and technical approaches.
- 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, Model Context Protocol, agent benchmarks, and security risks to AI agents.
- Experience in one or more of the following: 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.
- Experience evaluating frontier language or multimodal models.
- Experience with adversarial evaluations, robustness testing, or AI safety.
- Experience with distributed training, cloud ML infrastructure, or large-scale ML systems.
We don't expect candidates to have experience across every area above. We value deep ML expertise, strong experimental instincts, and the ability to quickly learn new techniques.
Compensation & Benefits- Salary Range: $130K–$200K, depending on experience and location
- Bonus: Performance-based annual bonus
- Professional Development: Support for conferences, continuing education, or leadership training
- Work Environment: Fully remote, U.S.-based
- Health Benefits: Comprehensive health, dental, and vision coverage
- Time Off: Generous PTO and paid holiday schedule
Skills Required
- 3-5+ years of professional experience building and deploying machine learning systems
- Strong proficiency in Python and modern ML frameworks like PyTorch and/or TensorFlow
- Experience training, fine-tuning, evaluating, and deploying ML models in production
- Experience designing evaluation methodologies and benchmarking systems
- Experience with MLOps tools
- Experience with cloud platforms such as Google Cloud Platform, AWS, or Azure
10a Labs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about 10a Labs and has not been reviewed or approved by 10a Labs.
-
Healthcare Strength — Benefits include comprehensive medical, dental, and vision coverage for full-time roles, listed across multiple postings. Coverage is presented as a core part of the package rather than a role-specific perk.
-
Leave & Time Off Breadth — Positions frequently advertise generous PTO and paid holidays, with some roles noting unlimited PTO and flexible hours. This indicates substantial time-off provisions alongside remote work arrangements.
-
Strong & Reliable Incentives — Compensation commonly includes performance-based annual bonuses and occasional spot bonuses. These incentives are presented as standard components for many roles.
10a Labs Insights
What We Do
10a Labs is an applied research and technology company specializing in AI security. We deliver intelligence collection, investigative research, and analysis for AI unicorns, Fortune 10 companies, and U.S. tech leaders.
