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Machine Learning Platform Engineer Jobs in Washington

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

... Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ... cloud platforms (AWS, GCP, Azure) and distributed systems. • Apply containerization and ...

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related ...

Tech Tammina LLC

MLOps Platform Engineer

Reston, VA · On-site

MLOps Platform Engineer Location: Reston VA Required Qualifications · 3+ years of hands-on ... machine learning workflows, including training, inference, and model monitoring. · Experience with ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

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 ...

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Machine Learning Platform Engineer information

What is a machine learning platform engineer?

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 does a machine learning platform engineer do?

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 skills and qualifications are needed to thrive as a machine learning platform engineer?

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 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:

Machine Learning Platform Engineer jobs near you
Infographic showing various Machine Learning Platform Engineer job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer

Chantilly, VA • On-site

Cymertek Corporation
IT Services • 11 - 50 employees
Learn more about Cymertek Corporationexternal

Full-time

Re-posted 10 days ago

Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. In this role, you will work with cutting-edge technologies to design, develop, and deploy machine learning models that solve complex problems and improve decision-making processes.
Responsibilities:
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
Qualifications:
Required:
• TS/SCI Full Poly (Please note this position requires full U.S. Citizenship)
• Bachelor's Degree
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
• Proficiency in programming languages (e.g., Python, R, Java)
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Expertise in model evaluation techniques and metrics
• Strong knowledge of version control tools (e.g., Git)
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
• Understanding of database technologies (e.g., SQL, NoSQL)
Preferred:
• Experience with natural language processing (NLP)
• Knowledge of deep learning techniques (e.g., CNNs, RNNs)
• Familiarity with deployment tools (e.g., Docker, Kubernetes)
• Experience with data augmentation and synthetic data generation
• Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
• Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sī-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.

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