Top Machine Learning Jobs in Washington, DC

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Leads the design, development, deployment, and optimization of scalable AI and generative AI solutions. Translates business needs into secure, production-ready architectures; applies foundation models, NLP, retrieval, vector search, and agentic workflows; and implements MLOps and LLMOps practices. Manages project workstreams, evaluates solution performance, ensures security and compliance, collaborates with stakeholders, and coaches junior team members.

The Data Scientist will support Army network and enterprise information environment missions by analyzing complex datasets, developing statistical and machine learning models, integrating APIs and automated data pipelines, and building Palantir Foundry and Army Vantage applications. The role includes creating executive visualizations, applying AIP tools, supporting secure Army and DoD data environments, and translating technical findings into actionable recommendations for senior leadership.

Analyze complex structured and unstructured datasets to answer client questions, evaluate AI and machine learning models, and deliver objective insights for leadership decisions. Collaborate with clients and teammates, mentor colleagues, and strengthen data science capabilities supporting Department of War or Intelligence Community clients. The role may involve GEOINT, LLMs, and all-source analysis in a classified environment.

Analyze structured and unstructured data to uncover insights, develop predictive models and algorithms, and create visualizations that support client decision-making. The role involves data exploration, cleaning, mining, statistical analysis, machine learning, artificial intelligence, and natural language processing across public- and private-sector challenges. Candidates collaborate with clients, use programming and distributed-computing tools, and must hold a Secret clearance and bachelor’s degree.

Build and operate scalable Golang backend services and APIs for a multimodal ML platform handling video, image, and document processing. Integrate ML/LLM inference, agentic workflows, and vector retrieval (Milvus). Deploy and manage services on Kubernetes with Terraform on AWS, ensure observability, reliability, and security, and collaborate with ML engineers to productionize pipelines and run on-call/incident response.

Develop data science capabilities by analyzing complex structured and unstructured data, evaluating AI/ML models, translating findings into actionable insights, collaborating with clients, and mentoring teammates. The role supports defense and intelligence clients and may involve GEOINT, LLMs, and all-source analysis.

Conducts data mining, statistical, predictive, and exploratory analyses for defense intelligence. Builds AI and machine learning tools, predictive systems, data architectures, visualizations, and data management solutions. Integrates disparate sources, optimizes data throughput and queries, identifies patterns and anomalies, and produces concise intelligence products. Collaborates with intelligence community members, works independently, supports program evaluation, and leads research into complex problems.

Conducts data analytics, engineering, mining, statistical analysis, predictive modeling, and intelligence-focused data visualization. Designs and optimizes data architectures, storage, access, integration, throughput, and query performance. Builds AI automation tools and prediction systems from disparate data sources, collaborates with intelligence community members, communicates complex findings, and develops concise defense intelligence products. Requires active TS/SCI clearance, U.S. citizenship, and ability to obtain a counterintelligence polygraph.

Develop and deploy machine learning models and statistical algorithms to detect financial crime using large-scale BSA/AML transaction data. Perform exploratory analysis, feature engineering, validation, SQL analysis, visualization, and documentation using Python, R, PySpark, AWS, and related tools. Collaborate with investigators, compliance analysts, and technical stakeholders to translate regulatory requirements into analytical solutions. The role requires active Top Secret clearance with SCI eligibility and full-time onsite work in Washington, DC.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

Develop and deploy NLP and machine learning models for classification, sentiment analysis, entity extraction, information retrieval, and user intent detection across large-scale legal, financial, news, and business datasets. Design scalable data science pipelines, evaluate modern AI algorithms and tools, translate business needs into technical solutions, and collaborate with product and engineering teams. Mentor junior scientists and contribute to model deployment, monitoring, maintenance, and development best practices.

Develops algorithms and analytical systems to interpret structured and unstructured data for government and private-sector clients. Applies statistical and scientific methods to deliver quantitative and qualitative insights, working collaboratively in data-rich environments. Responsibilities include data analysis, data gathering, cleansing, parsing, and translating complex datasets into objective answers that support informed decision-making.

Lead data science for defense clients: perform data engineering, mining, exploratory/predictive/statistical analysis; build ML/AI tools (recommendation engines, automated scoring); manage large, disparate data sources using R/Python/SQL; create visualizations in Power BI/Tableau; support Multi-INT analytics and provide senior-level analytic products for the defense cover program.

Develops advanced computational economics, econometric, statistical, and machine learning solutions for IMF-wide business and research needs. Designs scalable data pipelines, platforms, algorithms, and reproducible analytical workflows; improves computational performance and data reliability; evaluates emerging technologies; and creates technical documentation, applications, tutorials, presentations, and training for diverse audiences.

The Software Engineer, Applied AI will develop machine learning solutions and classification models, enhancing text, image, and video understanding on a policy intelligence platform.

Lead complex analytics projects for DoD/intelligence customers by developing and evaluating analytic methodologies, designing domain ontologies and knowledge graphs, applying semantic web standards, enabling semantic data retrieval and reasoning, integrating diverse data sources for interoperability, and guiding teams to produce actionable intelligence.

Design and lead end-to-end AI solution architectures, ensuring scalability, security, and compliance. Translate business and regulatory requirements into technical designs, evaluate tools/platforms, document architecture standards, coordinate technical teams, and support deployment and ongoing improvements.

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.

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.

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.

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.

Lead enterprise risk adjustment strategy using advanced analytics and ML to maximize risk score accuracy and reimbursement across Medicare Advantage, Medicaid Managed Care, and ACO REACH. Build predictive models, oversee data pipelines, run chart review programs, partner with clinical and finance teams, maintain audit-ready analytics, and present results to executive and board stakeholders.

Lead federal engagements to design compliant AI/NLP and RAG knowledge-management solutions. Develop integrations, influence product strategy, build relationships with agency leaders, support sales, and produce federal-focused technical materials.