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Remote Machine Learning Quant Jobs in Falls Church, VA

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

Strong understanding of experimental design, model evaluation, and quantitative analysis ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage

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 ...

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 ...

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

... 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 ...

New

Develop quantitative simulations and models to provide descriptive and predictive analytics ... Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ...

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Showing results 1-20

Remote Machine Learning Quant information

See Falls Church, VA salary details

$11.7K

$138.3K

$211.3K

How much do remote machine learning quant jobs pay per year?

As of Aug 20, 2026, the average yearly pay for remote machine learning quant in Falls Church, VA is $138,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $147,800.00 per year, depending on experience, location, and employer.

What is the difference between Remote Machine Learning Quant vs Remote Data Scientist?

AspectRemote Machine Learning QuantRemote Data Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or financeDegrees in data science, statistics, or related fields; certifications like CAP or DASCA
Work EnvironmentFinancial firms, hedge funds, or quantitative trading companiesTech companies, research institutions, or consulting firms
Industry UsageFinance, trading, hedge fundsTechnology, healthcare, marketing, finance
Common Search/ComparisonYesNo

Remote Machine Learning Quants focus on developing quantitative models for trading and investment strategies within financial firms, often requiring finance-specific knowledge. Remote Data Scientists work across various industries, applying data analysis and machine learning to solve diverse business problems. While both roles involve machine learning, Quants are more finance-oriented, whereas Data Scientists have broader industry applications.

What are popular job titles related to Remote Machine Learning Quant jobs in Falls Church, VA?

For Remote Machine Learning Quant jobs in Falls Church, VA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Quant jobs in Falls Church, VA look for?

The top searched job categories for Remote Machine Learning Quant jobs in Falls Church, VA are:

What cities near Falls Church, VA are hiring for Remote Machine Learning Quant jobs?

Cities near Falls Church, VA with the most Remote Machine Learning Quant job openings:

Infographic showing various Remote Machine Learning Quant job openings in Falls Church, VA as of August 2026, with employment types broken down into 6% Internship, 51% Full Time, 12% Part Time, and 31% Contract. Highlights an 100% Remote job distribution, with an average salary of $138,347 per year, or $66.5 per hour.

Machine Learning Engineer

10a Labs

Washington, DC • On-site, Remote

$130K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 17 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