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Machine Learning Platform Engineer Jobs in Washington

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Senior AI/ML Engineer

Great Falls, VA · Remote

$105K - $145K/yr

The successful candidate will bring a strong software engineering background, deep expertise in machine learning platforms, and practical experience operationalizing AI solutions from concept to ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

... Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of ... Cloud and Platform Engineering * Leverage AWS services including S3, EC2, Lambda, SageMaker, and ...

... Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of ... Cloud and Platform Engineering * Leverage AWS services including S3, EC2, Lambda, SageMaker, and ...

Prior hands-on experience with cloud platforms (AWS, Azure, GCP) and ML services (e.g., SageMaker ... Machine Learning, Artificial Intelligence, Data Science, Engineering, Mathematics, or a closely ...

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

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 ... Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML ...

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 ... Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML ...

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Machine Learning Platform Engineer information

What are the key skills and qualifications needed to thrive in the Machine Learning Platform Engineer position, and why are they important?

A Machine Learning Platform Engineer should have strong programming skills (especially in Python or Java), knowledge of machine learning frameworks (like TensorFlow or PyTorch), and experience with cloud platforms and scalable infrastructure. Familiarity with containerization tools (such as Docker and Kubernetes), CI/CD systems, and relevant certifications in cloud or machine learning technologies is highly valued. Effective problem-solving, teamwork, and clear communication are crucial soft skills for collaborating across data science and engineering teams. These capabilities enable seamless creation and maintenance of robust, high-performance machine learning platforms for scalable model development and deployment.

What does a typical day look like for a Machine Learning Platform Engineer?

A typical day for a Machine Learning Platform Engineer involves designing, building, and maintaining the infrastructure that supports data science and machine learning workflows. You might spend your time developing new features for the platform, optimizing data pipelines, deploying models, and troubleshooting technical issues alongside data scientists and engineers. Collaboration is key—you’ll often work closely with cross-functional teams to understand requirements, ensure scalability, and improve the overall machine learning lifecycle. This role offers a challenging mix of software engineering and system design, so adaptability and a proactive mindset are important for success.

What is a Machine Learning Platform Engineer job?

A Machine Learning Platform Engineer designs, builds, and maintains the infrastructure that enables machine learning development and deployment at scale. They work on areas like data pipelines, model training workflows, monitoring, and cloud or on-premises platforms to ensure ML models run efficiently in production. Their role bridges software engineering and machine learning, focusing on automation, scalability, and reliability to support data scientists and ML engineers in delivering models faster and more effectively.

What are popular job titles related to Machine Learning Platform Engineer jobs in Washington? For Machine Learning Platform Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Platform Engineer jobs in Washington look for? The top searched job categories for Machine Learning Platform Engineer jobs in Washington are:
Infographic showing various Machine Learning Platform Engineer job openings in Washington as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution.
Engineer, Machine Learning

Engineer, Machine Learning

Beyond SOF

Washington, DC • On-site

Full-time

Re-posted 2 days ago


Job description

Role Summary:
The Machine Learning Engineer is
responsible for developing and
implementing machine learning models
and algorithms to solve complex
problems.
Main Responsibilities and Duties:
Develop and implement machine
learning models and algorithms.
Collaborate with the engineering team to
integrate machine learning solutions into
projects.
Stay updated on the latest machine
learning technologies and trends.
Develop and implement quantum
machine learning models and
algorithms. Collaborate with quantum
engineers to integrate quantum
machine learning solutions into the
company's projects.