Top Machine Learning Jobs in Washington, DC

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.

Design, build, and optimize event-driven, distributed backend systems and APIs in Python for large-scale content metadata extraction and enrichment. Deploy and operate resilient AWS-based pipelines, collaborate with ML teams to integrate models, and ensure system performance, observability, and data integrity.

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

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

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.

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.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

As an Applied Machine Learning Scientist, you will innovate and develop machine learning algorithms, write production code, and collaborate to implement and test these solutions based on historical data.

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.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

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.

Work with clients to analyze structured and unstructured data, build data pipelines, develop predictive models and algorithms, and create visualizations to inform decision-making using ML/NLP and related tools.

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.

Lead strategy and hands-on architecture for large-scale digital transformations: conduct technology due diligence, define target-state architectures, evaluate platforms, design cloud and AI-enabled solutions, govern implementations, mentor teams, and ensure alignment between business objectives and delivery.

Partner with functional leaders to translate business strategy into people strategy. Own org design, performance management, compensation, talent development, engagement, and retention. Provide coaching on career pathing, change management, and sensitive employee issues. Use people data to generate insights and recommendations, build compliant HR policies, manage global employee relations, and collaborate with People Team COEs to deliver cohesive people programs at scale.

As a Manager of Cloud Software Engineering at Coupa, you will lead AI platform DevOps, manage global teams, and oversee agile delivery while ensuring technical quality and innovation.

Lead development of fraud-detection analytics and predictive models; perform data quality assessments; build scalable ML and NLP solutions; collaborate with investigators; produce documentation, visualizations, dashboards, and case leads; coordinate with data engineering and deliver findings to technical and executive stakeholders.

The Senior Software Engineer will design and optimize recommendation algorithms, maintain data pipelines, and improve personalized user experiences using machine learning techniques and backend engineering skills.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.