ZipRecruiter

Log In

1

Machine Learning Infrastructure Engineer Jobs in Washington

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Develop and maintain machine learning pipelines and infrastructure. * Stay current with the latest ...

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

We are seeking an earlycareer Machine Learning Engineer who is excited to grow rapidly by building ... Experience with cloud infrastructure and managing resources in the cloud. * Master's degree in a ...

Beyond SOF

Engineer, Machine Learning

Washington, DC

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 ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

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 ...

Molg

Infrastructure Engineer

Sterling, VA · On-site

$106.50K - $139.60K/yr

As an Infrastructure Engineer, you will: * Own the design, deployment, and operation of Molg ... in learning how to use our various pieces of equipment and machinery is taught and can gain the ...

Ametek

Machine Learning Engineer

Herndon, VA · On-site

We are seeking an early-career Machine Learning Engineer who is excited to grow rapidly by building ... Experience with cloud infrastructure and managing resources in the cloud. * Master's degree in a ...

Steampunk

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Steampunk

Machine Learning Engineer

Mclean, VA

$115K - $150K/yr

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data Scientists and Engineers to use AI/ML technology in supporting Federal use cases. We are looking for a ...

next page

Showing results 1-20

People also search for

All JobsMachine Learning Infrastructure Engineer JobsMachine Learning Infrastructure Engineer Jobs in Washington

Machine Learning Infrastructure Engineer information

See Washington salary details

$52.7K

$143.9K

$206.1K

How much do machine learning infrastructure engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning infrastructure engineer in Washington is $143,915.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,800.00 and $159,700.00 per year, depending on experience, location, and employer.

What is a Machine Learning Infrastructure Engineer job?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

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

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by Machine Learning Infrastructure Engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.
More about Machine Learning Infrastructure Engineer jobs
What are popular job titles related to Machine Learning Infrastructure Engineer jobs in Washington? For Machine Learning Infrastructure Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Infrastructure Engineer jobs in Washington look for? The top searched job categories for Machine Learning Infrastructure Engineer jobs in Washington are:
What cities in Washington are hiring for Machine Learning Infrastructure Engineer jobs? Cities in Washington with the most Machine Learning Infrastructure Engineer job openings:
Machine Learning Infrastructure Engineer jobs near you
Infographic showing various Machine Learning Infrastructure Engineer job openings in Washington as of May 2026, with employment types broken down into 86% Full Time, 8% Part Time, 5% Contract, and 1% Summer. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $143,915 per year, or $69.2 per hour.
Senior Machine Learning Engineer, Public Sector

Senior Machine Learning Engineer, Public Sector

Scale AI

Washington, DC • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
Scale AI is committed to developing reliable AI systems for critical decisions, and they are seeking a Senior Machine Learning Engineer to enhance their products and customer experience. The role involves leveraging advanced AI techniques to deploy models in government systems and improve machine learning infrastructure.
Responsibilities:
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• This role will require an active security clearance or the ability to obtain a security clearance
Qualifications:
Required:
• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Solid background in algorithms, data structures, and object-oriented programming
• Strong programming skills in Python, experience in Tensorflow or PyTorch
• This role will require an active security clearance or the ability to obtain a security clearance
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
Preferred:
• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
• Experience with computer vision, generative AI models, large language models, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

Apply