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Remote Machine Learning Neuroscience Jobs in Washington

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Comcast

Engineer 3, Machine Learning-5125

Washington, DC · On-site +1

$126K - $165K/yr

... for the remote option.) Job Summary DUTIES: Contribute to a team responsible for building ... train Machine Learning models, including Deep Learning models, using TensorFlow, PyTorch ...

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Infographic showing various Remote Machine Learning Neuroscience job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer

10a Labs

Washington, DC • On-site, Remote

$130K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 19 days ago

Job description

About the Role

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.
What We're Looking For
  • 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.
Nice to Have
  • 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

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