Top Senior Machine Learning Jobs in Washington, DC

Build and own production Vision AI systems end to end, including model selection, inference pipelines, evaluation, monitoring, and customer-facing features. Shape architecture, collaborate with product, design, and engineering teams, and use AI coding tools to accelerate development. Establish high standards for quality, testing, reliability, security, and privacy while mentoring engineers and taking ambiguous ideas from prototype to production.

Lead AI and autonomous vehicle behavior safety strategy for Level 3–4 automated driving systems. Own behavior safety claims, evidence criteria, validation methodologies, performance indicators, and launch-readiness assurance. Evaluate ML-driven AV performance using simulation, closed-course, and public-road data. Define safety metrics and strategies for imitation and reinforcement learning systems, interpret applicable standards, and influence cross-functional engineering teams and executives.

Leads the development and operation of a comprehensive insider threat program supporting classified national security missions. Establishes compliant policies, metrics, monitoring, detection, investigations, training, and response processes; manages analysts and coordinates with Security, Cybersecurity, HR, Legal, government agencies, counterintelligence, and law enforcement. Oversees technology integration, behavioral indicators, threat hunting, risk assessments, reporting, and awareness exercises while protecting employee privacy and civil liberties.

Provides principal-level ServiceNow consulting, architecture, engineering, and delivery oversight for enterprise clients. Leads technical solution design, implementations, automation, cloud deployment, presales estimation, workshops, and client advisory activities. Establishes technical standards, mentors engineers and architects, supports governance and practice growth, and serves as an escalation point. The role also develops AI-enabled ServiceNow offerings and requires approximately 10% travel.

Build and tune fraud detections across accounts, authentication, payments, and other high-risk flows. Lead threat hunts, identify emerging abuse patterns, improve fraud telemetry, and convert findings into automated, tested detections. Develop tools, dashboards, and enrichment for fraud operations; measure precision, recall, coverage, and detection speed; and collaborate with security, engineering, risk, product, and operations teams to address systemic fraud risks.

Develop and lead complex AI and data science solutions, shape AI technical strategy, research emerging technologies, resolve large-scale technical problems, and guide cross-functional teams. The role focuses on scalable data solutions, machine learning, deep learning, large language models, generative AI, NLP, computer vision, Python, and Vertex AI. It requires a bachelor's degree and at least five years of progressive data analytics and data science experience.

Lead teams building Samsara Assistant, Agent Studio, and agent extensibility. Own product growth, activation, answer quality, trust, repeat usage, and proactive agent capabilities. Set technical direction for an AI platform used by customers and internal product teams, partner across Safety and Maintenance, and lead approximately 10 machine learning, applied science, and full-stack engineers through two tech leads. Hire, develop, and manage a high-performing engineering organization.

Lead deployment and adoption of Altana’s software platform for U.S. government customers. Serve as a trusted advisor to agency leaders, coordinate implementation and engineering teams, translate customer feedback into product requirements, drive mission outcomes, and identify account expansion opportunities. The role requires technical delivery or public-sector consulting experience, strong stakeholder management, data-informed decision-making, and the ability to communicate technical and commercial value. It is based in Washington, DC, or Brooklyn, NY, with hybrid flexibility.

Lead and transform the Fraud Intelligence Team into a high-impact function by improving operating models, QA, tooling, and metrics; build entry-level talent programs; connect labeling to measurable fraud prevention outcomes; deliver actionable insights to Product, R&D, Analytics, and GTM; and leverage AI and automation to increase productivity and business impact.

Lead product strategy, roadmap, and execution for Zscaler’s threat detection and response offerings within its Agentic SOC and MDR business. Translate threat intelligence and customer needs into innovative security products, coordinate engineering and go-to-market teams, and measure product impact. The role owns commercialization, technical direction, product quality, and business outcomes while requiring deep cybersecurity expertise and experience with enterprise security products.

Lead Amazon performance marketing strategy and execution, manage Sponsored Ads and DSP, collaborate with agencies and cross-functional teams, optimize campaigns and budgets, analyze performance with AMC/analytics, and measure commercial impact to drive ROAS and customer acquisition.

Leads complex, cross-functional technical programs for the Superintelligence Lab. Responsibilities include roadmap execution, milestone and dependency management, risk mitigation, issue resolution, stakeholder alignment, leadership reporting, and implementing program-management best practices. The role requires collaboration with engineering, data science, and leadership teams while using AI technologies and Jira to improve workflows, decision-making, and business outcomes.

Investigate complex AML cases, review transaction-monitoring alerts, determine SAR/STR filing decisions, and communicate findings to regulators, law enforcement, and stakeholders. The role also supports audits, improves AML detection models and typology coverage, analyzes transactional data, identifies financial crime trends, and provides analyst training. Candidates need strong blockchain, AML regulations, investigative writing, and blockchain forensic tool experience, with AI and SQL capabilities preferred or advantageous.

Lead firmware and embedded software development for AI-powered video safety products. Architect scalable embedded systems, integrate camera and real-time edge computing capabilities, deploy CV/ML models, and guide technical decisions. Collaborate with hardware, cloud, machine learning, and product teams on next-generation devices and complex multi-team projects. Maintain production systems, improve testing and release infrastructure, mentor engineers, and support products from development through mass production.

Lead the design and implementation of AI initiatives for edge devices. Develop and optimize machine learning solutions using large-scale sensor, video, text, diagnostic, transaction, and location data. Partner with engineering and business teams to prototype AI experiences, ship production systems, adopt research advances, and improve edge model performance. Mentor ML engineers and communicate technical concepts to varied audiences.

Own the full sales cycle for enterprise B2B demand-generation clients across EMEA and the US. Responsibilities include prospecting, building outbound pipelines, developing account strategies, engaging executive buyers, negotiating complex contracts, closing net-new business, expanding accounts, forecasting accurately, and collaborating with delivery, data, media, marketing, and client success teams.

Manage technical projects and enduring programs that turn concepts into working prototypes. Responsibilities include requirements definition, operations analysis, test planning, process design, technology roadmaps, intellectual property, academic partnerships, R&D opportunity development, and IRAD budget management. The role requires technical credibility in areas such as autonomy, robotics, RF/EW, machine learning, or aerospace, plus strong project management, communication, and process-building skills.

Leads AI and automation product strategy for disability and absence claims operations. Responsibilities include prioritizing AI opportunities, owning roadmaps, designing human-in-the-loop workflows, defining safeguards and success metrics, partnering with engineering, coaching Product Owners, managing delivery increments, and communicating operational impact to senior leadership.

Owns strategic planning, governance, prioritization, risk management, and execution across a portfolio of Superintelligence Lab programs. The role establishes phase-gate standards, manages change, tracks portfolio health through dashboards and metrics, resolves blockers, advises cross-functional teams, and communicates progress to executives. It requires strong technical program management experience, Jira proficiency, Agile and SDLC knowledge, and the ability to apply AI technologies to improve business outcomes.

Lead go-to-market execution for Samsara’s AI products as an enterprise overlay seller. Partner with account executives and account development representatives to develop pipeline, architect complex deals, run high-touch pilots, demonstrate customer ROI, and support early adoption. Collaborate with product and go-to-market teams to shape the roadmap while creating scalable sales frameworks. The role requires complex full-cycle sales experience, AI commercial-model expertise, quota overachievement, and success navigating large, multi-stakeholder enterprise transactions.

Own and grow strategic enterprise customer relationships, driving retention, renewals, expansion, and seven-figure software transactions. Develop multi-year account plans, build executive and technical stakeholder relationships, identify expansion opportunities, lead negotiations, maintain forecasts and pipeline visibility, and coordinate cross-functional teams. Engage with data scientists and AI/ML engineers to understand adoption, customer outcomes, and opportunities to expand platform usage across business units and use cases.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Analyzes the Security for AI competitive landscape, including AI detection and response, generative AI security, autonomous agents, prompt injection, and data leakage. Partners with Product, Sales, Marketing, Strategy, and senior leaders to guide product roadmaps, go-to-market strategy, deal support, sales tactics, and competitive positioning. Conducts win/loss analysis and translates complex AI and cybersecurity concepts into executive and field-actionable guidance.