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Flexible Remote Machine Learning Engineer Jobs in Washington, DC

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 ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer (IC)

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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All JobsMachine Learning Engineer JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in Washington, DC

Flexible Remote Machine Learning Engineer information

See Washington, DC salary details

$35.7K

$145.8K

$219.2K

How much do flexible remote machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for flexible remote machine learning engineer in Washington, DC is $145,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $175,600.00 per year, depending on experience, location, and employer.

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

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

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are the most commonly searched types of Remote Machine Learning Engineer jobs in Washington, DC?

The most popular types of Remote Machine Learning Engineer jobs in Washington, DC are:

What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Washington, DC?

For Flexible Remote Machine Learning Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Washington, DC look for?

The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Washington, DC are:

Flexible Remote Machine Learning Engineer jobs near you

Machine Learning Engineer

10a Labs

Washington, DC • On-site, Remote

$130K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 16 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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