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 AI technology integration and deployment within the tax practice. Oversees data infrastructure, pipelines, modeling, quality validation, and multi-source integration. Develops Python-based analytics solutions using machine learning and natural language processing, conducts rapid experimentation, and drives data-informed innovation. Coaches and develops high-performing teams while collaborating with stakeholders and advising on strategic initiatives.

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

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.

Lead design and delivery of AI and GenAI data solutions for Tax, including analytical modeling, prompt engineering, ML/NLP, Azure AI Services, LangChain, and RAG. Manage and coach teams, validate outcomes with clients, and translate raw data into actionable insights to drive business growth.

Lead design, development, and deployment of AI/GenAI solutions for Tax. Build end-to-end AI architectures using Azure AI Services and Python, apply ML/NLP and LLMOps, manage vector databases and agent systems, evaluate LLMs, and mentor project teams to deliver data-driven insights.

Lead product vision and roadmap for the Hivemind AI Platform to enable training, evaluation, governance, and safe edge deployment of foundation and domain models. Drive MLOps, data/simulation pipelines, synthetic data generation, model governance, and integration with edge hardware. Partner cross-functionally to productionize research, ensure accreditation and safety, and support continuous learning and sovereign AI factory capabilities for mission-critical autonomy.

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.

Use data exploration, cleaning, modeling, and visualization to turn structured and unstructured data into actionable insights. Develop predictive models and algorithms, apply ML/AI/NLP and text-mining techniques, and collaborate with clients to solve real-world problems.

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.

Designs, builds, deploys, and integrates production-grade AI and machine learning systems for Defense and Intelligence clients. Responsibilities include architecting scalable solutions, training and deploying multimodal models, optimizing ML systems, implementing MLOps, and integrating software into mission environments. The role may involve cloud platforms, containerization, data brokering, client engagements, and business development.

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.

Pre-sales technical lead for federal accounts who builds and delivers AI/ML and GenAI demos, designs compliant solutions (FedRAMP/DoD IL/NIST/FISMA), supports pilots/proofs, advises on data readiness and security, and partners with sales to drive federal adoption.

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.

Develops advanced economic, econometric, and machine learning models for IMF business needs. Responsibilities include designing algorithms, optimizing parallel and distributed computations, building scientific computing programs and reusable libraries, supporting analytical environments, conducting computational economics research, and training professionals in modeling techniques and software.

Leads advanced analytics and data science initiatives supporting federal communications, outreach, stakeholder engagement, and mission performance. Develops predictive models, forecasts, anomaly detection, dashboards, reporting frameworks, and measurement methodologies. Translates complex data into leadership recommendations, supports data pipelines and workflow automation, ensures governance and quality, and mentors team members. Collaborates with communications, UX, technology, and governance stakeholders while implementing machine learning and generative AI solutions in cloud environments.

Leads advanced data science and analytics initiatives using statistics, modeling, machine learning, and business analysis. Develops scalable policy-adherence metrics and valuation models using complex structured and unstructured healthcare data, including claims and denials. Creates reports, projections, and presentations; advises executives; manages stakeholders; and influences roadmap and implementation decisions across compliance, contracting, Medicaid, and business teams.

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.

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.