Top Machine Learning Jobs in Washington, DC

Work with clients to analyze large, structured and unstructured data sets, design and test AI/ML models, mentor teammates, and deliver actionable insights to leadership, primarily supporting DoW/IC customers.

Lead and mentor ML engineering teams building and maintaining production ML products (research-to-production, training/inference pipelines, MLOps). Partner with product, define processes, and ensure reliable shipping and operations in a hybrid, distributed environment.

Summer data science internship working on ML projects (anomaly detection, numerical optimization, PII/PHI NLP). Interns will develop models, write high-quality Python, use Linux and development tools, work with git, Docker, CI/CD and Kubernetes, participate in code reviews and agile rituals, and present results to technical and non-technical audiences.

Develop and productionize AI features from PoC to scalable deployments. Write production-ready Python code, implement testing and debugging, refine user stories, participate in ethical and security reviews, and collaborate with stakeholders to align AI solutions with business needs.

Summer internship working on applied data science projects (e.g., anomaly detection, numerical optimization, PII/PHI NLP). Responsibilities include end-to-end model development, writing modular Python code, using Linux and development tools, containerization and deployment basics, participating in code reviews and agile rituals, and clearly presenting results to technical and non-technical audiences.

Design, build, deploy, and maintain AI/ML models for immigration-related datasets in classified AWS environments. Analyze complex data, operationalize models via DevSecOps CI/CD and containerization, present results, and provide security architecture and identity-management technical leadership for a cleared federal customer.

The Senior Analyst will develop AI and ML algorithms, optimize data systems, and present research findings. Requires extensive experience in model development, system architecture, and MLOps.

Design, train, test, deploy, and maintain machine learning models for DoD-focused solutions. Collaborate with data engineers, data scientists, and product owners to implement ML, deep learning, computer vision, and generative AI use cases while advising clients on algorithms, tools, and deployment.

Develop and innovate machine learning algorithms to maximize advertising ROI, prototype and test models on historical data, and implement production-ready code in collaboration with Data Engineers to scale solutions across a high-throughput programmatic advertising platform.

Work with clients to analyze large structured and unstructured data sets, develop and evaluate AI/ML models, mentor teammates, and deliver actionable insights to leadership. Support DoW/IC customers and translate complex data into decision-ready products.

Perform data exploration, cleaning, analysis, and visualization; develop and document predictive models and quantitative analyses; apply machine learning/AI to IoT and other data; work with clients to define problems and deliver actionable insights; conduct quantitative social science analyses and produce client-facing reports.

Lead end-to-end technical programs for ML infrastructure (inference, serving, efficiency, endpoints). Coordinate cross-functional teams, prioritize overlapping projects, manage timelines, budgets and scope, drive incident management and continuous improvement, and communicate status to engineering and leadership.

Design, train, test, deploy, and maintain ML models for defense customers. Collaborate with data engineers, scientists, architects, and product owners to implement deep learning, computer vision, and generative AI solutions and guide AI strategy for mission-critical systems.

Design, train, test, deploy, and maintain machine learning models for defense-focused solutions. Collaborate with data engineers, data scientists, and product teams to implement deep learning, computer vision, and generative AI use cases and support clients across the DoD market. Maintain model development and data handling pipelines.

Design, build, and deploy production ML and GenAI solutions from prototyping through serving. Apply supervised/unsupervised/deep learning and NLP to structured and unstructured data, implement data pipelines and feature engineering, evaluate model performance/bias/drift, and collaborate with engineers and product teams to integrate models into services and APIs while contributing to architecture, scalability, and documentation.

Build and deploy credit risk models for acquisition and account management. Create datasets and features from traditional and non-traditional sources, collaborate with credit, product, and engineering partners, run experiments, and monitor models in production to enable responsible lending decisions.

Design and implement AI solutions for Marine Corps needs, develop algorithms, mentor team members, and create scalable data platforms. Requires collaboration in a team environment.

Design and scale real-time bidding systems and bid forecasting; develop ML, reinforcement learning, and control-based bidding and pacing algorithms; analyze marketplace dynamics; run offline evaluations and online A/B experiments; collaborate with product, infrastructure, and engineering teams to deliver measurable advertiser ROI.

Six-month on-site co-op building LLM-driven features and agents inside the Nuclear Operating System. Ship ML models and agent workflows, develop data pipelines (Foundry/AWS GovCloud), build predictive and anomaly-detection models on time-series sensor data, and own model quality, evals, and monitoring for production readiness.

Six-month on-site Fall 2026 co-op building ML and LLM-driven features and agents inside the Nuclear Operating System. Responsibilities include shipping models and agent workflows, building data pipelines and integrations (Foundry, AWS GovCloud), developing predictive/time-series models, and owning model quality, evals, and monitoring to keep AI features production-ready and audit-ready.

Build and ship ML and LLM-driven features and agents inside the Nuclear Operating System (NOS). Develop data pipelines and integrations (e.g., Foundry, AWS GovCloud), create predictive and anomaly-detection models, and own model quality with evals, regression suites, and monitoring. Work on production systems alongside engineers and domain experts during a summer on-site internship.

Design, train, test, deploy, and maintain ML models (including generative and agentic AI) for DoD missions. Collaborate with engineers, scientists, and product owners to implement solutions, handle data and model development, and advise clients on ML strategy.

Provide technical leadership for AI/ML development under DMA/CIO7 tasks; design, develop, and deploy advanced AI/ML and agentic AI capabilities; ensure compliance with DIA QAF including model validation, bias testing, and performance optimization; coordinate with data scientists, software engineers, and mission stakeholders; recommend emerging AI/ML solutions.

Lead design and delivery of LLM- and agent-driven products end-to-end: build distributed agentic systems, retrieval and grounding pipelines, production inference stacks, evals and labeled-data flywheels, and partner cross-functionally to harden ML into reliable, mission-critical services.

The AI/Machine Learning Engineer will design, develop, and deploy AI models for healthcare, collaborating with teams to enhance patient outcomes using advanced data analytics and machine learning techniques.