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Remote Senior Machine Learning Engineer Jobs in Washington, DC

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

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Showing results 1-20

Remote Senior Machine Learning Engineer information

See Washington, DC salary details

$85.5K

$162.3K

$217.5K

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

As of Jul 15, 2026, the average yearly pay for remote senior machine learning engineer in Washington, DC is $162,292.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,700.00 and $182,900.00 per year, depending on experience, location, and employer.

How do Remote Senior Machine Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually, often including bonuses and stock options. Such compensation typically requires a strong educational background, a track record of impactful projects, and expertise in tools like TensorFlow or PyTorch.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

What are the key skills and qualifications needed to thrive as a Remote Senior Machine Learning Engineer, and why are they important?

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What does a Remote Senior Machine Learning Engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

What engineers make $300,000 a year?

Senior machine learning engineers can earn $300,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and work at large tech companies or in specialized industries. Compensation often includes base salary, bonuses, and stock options, particularly in high-demand markets.

Will MLE be replaced by AI?

As a Senior Machine Learning Engineer, the role involves designing, developing, and maintaining AI systems, which currently require human expertise. While AI tools can automate certain tasks, the need for skilled professionals to interpret data, ensure ethical use, and improve models remains essential. AI is more likely to augment rather than replace the responsibilities of MLEs in the foreseeable future.

What engineers make $200,000 a year?

Senior machine learning engineers often earn $200,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and proficiency with tools like TensorFlow or PyTorch. Compensation can vary based on industry, location, and company size, with some roles in tech giants or specialized fields reaching or exceeding this level.
What job categories do people searching Remote Senior Machine Learning Engineer jobs in Washington, DC look for? The top searched job categories for Remote Senior Machine Learning Engineer jobs in Washington, DC are:
Infographic showing various Remote Senior Machine Learning Engineer job openings in Washington, DC as of July 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 100% Remote job distribution, with an average salary of $162,292 per year, or $78 per hour.
AI/Machine Learning Engineer

AI/Machine Learning Engineer

Initiate Government Solutions

Washington, DC • Remote

$129K - $155K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

Description

Founded in 2007, Initiate Government Solutions (IGS) is a Woman-Owned Small Business and a fully remote IT services provider supporting federal partners nationwide. We deliver innovative Enterprise IT and Health Services solutions with a strong focus on data analytics, health informatics, cloud migration, AI, and the modernization of federal information systems.


Our vision is to be a health IT trendsetter, continuing to solve the nation's most challenging healthcare IT issues by conceiving, designing, and building solid, creative, and innovative open-source solutions. 


Our mission is to innovate, design, and deliver tailored solutions that balance technical advancement with cost-awareness while providing exceptional service.


IGS is currently pipelining for a remote AI/Machine Learning Engineer to support our work within the federal healthcare industry.  Candidates will be contacted as opportunities become available for further consideration. 


Assignment of Work and Travel:

This is a remote access assignment. The Candidate will work remotely daily and will remotely access VA systems and therein use approved VA provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested.


The AI/Machine Learning Engineer will work alongside a team of highly skilled developers and engineers in the development of AI applications. A motivated and qualified candidate will not only have hands-on development experience in (JavaScript, Python or Java) but also a willingness to collaborate with teams to solve problems. Together we're accelerating our client's digital transformation through the building and deployment of data-driven, scalable AI solutions.


Responsibilities and Duties (Included but not limited to):

  • Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
  • Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
  • Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
  • Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA's Lighthouse API, Azure Government, AWS GovCloud).
  • Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
  • Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
  • Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
  • Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
  • Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
  • Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
  • Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
  • Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
  • Monitor deployed models for drift, accuracy, and operational effectiveness over time.
  • Maintain model retraining schedules based on new data inputs or policy changes.
  • Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
  • Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools. 

Requirements

  • Bachelor's degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
  • 4+ years of experience in software and machine learning engineering.
  • Strong knowledge of natural language processing (NLP) and transformer models.
  • 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
  • Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
  • Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
  • Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
  • Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
  • Passion for developing team-oriented solutions to complex engineering problems 
  • Excellent communication skills and attention to detail
  • Analytical mind and problem-solving aptitude
  • Ability to obtain and maintain a Public Trust
  • Strong organizational skills

Preferred Qualifications and Core Competencies:

  • Master's degree in one of the above-mentioned fields
  • Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
  • Active VA Public Trust
  • Prior experience supporting a VA program
  • Prior, successful experience working in a remote environment

Successful IGS employees embody the following Core Values:

  • Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers. 
  • Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers' matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers' and end-users' business drivers and challenges to ensure solutions meet not only technical needs but also support their mission.
  • Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done. 
  • Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems.

Compensation: There are a host of factors that can influence final salary, including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.


Benefits: Initiate Government Solutions offers competitive compensation and a robust benefits package, including comprehensive medical, dental, and vision care, matching 401K and profit sharing, paid time off, training time for personal development, flexible spending accounts, employer-paid life insurance, employer-paid short and long term disability coverage, an education assistance program with potential merit increases for obtaining a work-related certification, employee recognition, and referral programs, spot bonuses, and other benefits that help provide financial protection for the employee and their family.


Initiate Government Solutions participates in the Electronic Employment Verification Program.Â