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Ml Engineer Jobs in Washington (NOW HIRING)

BTree Solutions, Inc.

AI/ML ENGINEER

Reston, VA · On-site

AI/ML ENGINEER Location: Reston,VA Duration: 12+ Months Visa: USC, GC, H1B and EAD Contract Type: W2 We are seeking a highly skilled and motivated AI/ML Engineer to join our team and drive the ...

Interon IT Solutions

AI/ML Engineer

Reston, VA · On-site

AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate Requirement: Local to East Coast only Client is seeking an AI/ML Engineer to design and deliver end ...

Node.Digital

AI/ML Engineer

Arlington, VA

AI/ML Engineer Location: Arlington, VA Must have an active Top Secret Clearance Node is supporting a U.S. Government customer to provide support for onsite incident response to civilian Government ...

Assured Consulting Solutions

AI/ML Engineer

Reston, VA · On-site

$175K - $220K/yr

Our AI/ML Engineer is the core mission specialist who develops, implements, and deploys innovative AI/ML and LLM-enabled capabilities to solve mission-critical problems. This role combines deep model ...

Node.Digital

AI/ML Engineer

Arlington, VA · On-site

AI/ML Engineer Location: Arlington, VA Must have an active Top Secret Clearance Node is supporting a U.S. Government customer to provide support for onsite incident response to civilian Government ...

Mind Ware Inc

AI/ML Engineer

Reston, VA · On-site

AI/ML Engineer Location: Reston, VA (Onsite - 5 Days/Week) Employment Type: Full-Time Job Summary We are seeking a highly skilled AI/ML Engineer . The ideal candidate will have strong experience in ...

540

AI/ML Engineer

Arlington, VA

540 is seeking an AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and ...

Node.Digital

AI/ML Engineer

Arlington, VA · On-site

AI/ML Engineer Location: Arlington, VA Must have an active Top Secret Clearance Node is supporting a U.S. Government customer to provide support for onsite incident response to civilian Government ...

540

AI/ML Engineer

Arlington, VA · On-site

540 is seeking an AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and ...

540

AI/ML Engineer

Arlington, VA

540 is seeking an AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and ...

Synergy ECP

AI/ML Engineer

Annapolis Junction, MD · On-site

They are seeking AI/ML Engineers to build, deploy, and maintain machine learning models and data-driven systems at scale, collaborating with software and DevOps teams for integration and monitoring ...

Assured Consulting Solutions

AI/ML Engineer

Reston, VA · On-site

They are seeking an experienced AI/ML Engineer to develop and implement AI/ML capabilities for mission-critical problems, focusing on model training and deployment. The role involves collaborating ...

System One

AI/ML Engineer

Mclean, VA · Remote

AI/ML Engineer Location: Remote Work Authorization: Must be able to work without sponsorship Clearance Requirement: Must be able to obtain and maintain a Federal or DoD Public Trust Position Overview ...

540

Senior AI/ML Engineer

Arlington, VA · On-site

$120K - $165K/yr

540 is seeking a Senior AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will lead the design and evolution of production AI/ML services and ...

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Showing results 1-20

All JobsMl Engineer JobsMl Engineer Jobs in Washington

Ml Engineer information

See Washington salary details

$37.4K

$101K

$160.8K

How much do ml engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for ml engineer in Washington is $101,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,300.00 and $123,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often find opportunities in tech, finance, healthcare, and other sectors investing in AI solutions.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.
What are the most commonly searched types of Ml Engineer jobs in Washington? The most popular types of Ml Engineer jobs in Washington are:
What are popular job titles related to Ml Engineer jobs in Washington? For Ml Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Ml Engineer jobs in Washington look for? The top searched job categories for Ml Engineer jobs in Washington are:
What cities in Washington are hiring for Ml Engineer jobs? Cities in Washington with the most Ml Engineer job openings:
Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Washington as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $101,009 per year, or $48.6 per hour.

AI/ML ENGINEER

BTree Solutions, Inc.

Reston, VA • On-site

Contractor

Re-posted 20 days ago

Job description

Job Title: AI/ML ENGINEER
Location: Reston,VA
Duration: 12+ Months
Visa: USC, GC, H1B and EAD
Contract Type: W2
We are seeking a highly skilled and motivated AI/ML Engineer to join our team and drive the development and optimization of AI solutions. This role is ideal for someone who thrives at the intersection of machine learning, large language models (LLMs), and cloud infrastructure. You will collaborate closely with business stakeholders to design, build, and refine intelligent systems that leverage cutting-edge technologies.
Key Responsibilities
  • Collaborate with business teams to understand requirements and translate them into ML models and prompt-based solutions.
  • Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.
  • Optimize and adapt prompt engineering strategies to improve model performance and relevance.
  • Integrate and deploy models using AWS services including Bedrock, S3, ECS, EC2, Lambda and other AI/ML related services.
  • Build and maintain scalable data pipelines and APIs to support ML workflows.
  • Monitor model performance and iterate based on feedback and metrics.
  • Stay current with advancements in AI/ML and cloud technologies to ensure our solutions remain cutting-edge.

Required Qualifications
  • Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
  • 3+ years of experience in machine learning, data science, or AI engineering.
  • Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
  • Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Deep experience with AWS services, especially Bedrock, S3, EC2, and Lambda
  • Familiarity with MLOps practices and tools for model deployment and monitoring.
  • Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
  • Strong programming skills in data analytics related languages and libraries, such as Python, R, Pandas, or JavaScript.
  • Experience with AWS SageMaker for model development and model deployment.
  • Understanding of quantitative/statistical/ML/AI modeling methodologies.
  • Experience in ML engineering, including hands-on experience with Generative AI/LLMs.
  • Experience with developing and deploying AI Agents for business problems.

Preferred Qualifications
  • Experience with fine-tuning or customizing foundation models.
  • Knowledge of data privacy and security best practices in cloud environments.
  • Familiarity with containerization (Docker) and container orchestration is a plus.

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