Top Senior Machine Learning Jobs in Washington, DC

Design, develop, secure, and modernize scalable omnichannel APIs supporting member-facing applications. Improve API security, resiliency, performance, and observability; apply AI-assisted engineering; collaborate with architecture, security, cloud, product, and operations teams; deliver proofs of concept, reusable patterns, and provide Tier 3 production support and incident response.

Design and implement scalable data architectures and analytical solutions for Air Force Mission Assurance. Integrate enterprise data platforms, develop AI/ML workflows, enable automation, and translate insights into decision-support products while supporting governance and system sustainment.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

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.

Lead product vision, strategy, and roadmap for Citian's transportation SaaS. Collaborate with engineering, design, data science, and GTM to build AI-driven features, validate solutions with clients, define success metrics, and drive adoption.

Lead the design, development, and deployment of scalable digital platforms and AI-enabled solutions. Mentor engineers and collaborate with cross-functional teams on technical architecture and engineering vision.

The Engagement Manager leads client projects, manages teams, ensures timely delivery, develops client relationships, identifies business opportunities, and provides thought leadership.

Lead technical direction and delivery of ML platform infrastructure (feature store, model serving, experimentation, training pipelines). Drive architecture, resolve system-level issues, write production code, mentor engineers, and partner with ML, data, and product teams to enable scalable, reliable ML model development and deployment.

The Engagement Manager manages project execution, collaborates with technical teams on AI solutions, develops client relationships, and coaches consultants.

Design, build, and scale event-driven, distributed backend systems in Python to extract and enrich metadata at massive scale. Lead architecture, mentor engineers, integrate ML/LLM components, optimize performance, and ensure observability and reliability across AWS-based pipelines.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.

The Director will manage AI software deployments, lead teams, handle client relationships, oversee project management, and drive business growth through new opportunities.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Drive enterprise software revenue by prospecting, closing, and expanding accounts. Build long-term pipeline, meet license/support/service targets, orchestrate complex multi-stakeholder deals, leverage channels, position machine learning and predictive analytics, and collaborate cross-functionally to deliver customer value.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Product Manager will lead the integration of airline and third-party partners, optimize supply metrics, and leverage AI for automation. Responsibilities include managing APIs, collaborating with engineering, and improving the booking experience.

The Chief Enterprise Architect will oversee the design and integration of cloud and data architecture solutions for government projects, ensuring alignment with industry standards and best practices.

Serve as a customer-facing technologist partnering with sales to position, demo, and package Forrester AI solutions; translate technical AI capabilities into business value, support deal structuring and negotiations, develop enablement and adoption assets, gather product feedback from the field, and drive client retention through training and value realization.

Develop and integrate advanced RF digital signal processing algorithms to detect, classify, track, and geolocate RF emissions. Work with recorded and synthetic I/Q data, SDR hardware (including RFSOC), and host processing platforms. Support algorithm modeling, software integration, testing, and field demonstrations while collaborating with cross-functional teams.

Lead execution of complex transformation workstreams: develop initiative workplans, perform hypothesis-driven analysis, build financial/business models, manage stakeholders, produce executive-level communications, and drive technology-enabled change and program delivery across healthcare lines of business.

Lead zero-to-one transformation of Scribd's knowledge platform using ML/LLMs. Set product vision, roadmap, and success metrics; prioritize trade-offs; partner with Design, Engineering, ML, and Data Science; deliver incremental improvements and extensible platform capabilities; drive cross-functional alignment and measure core user journeys.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.