Top Senior Machine Learning Jobs in Washington, DC

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.

Develop and maintain large housing datasets and infrastructure for US housing policy research. Responsibilities include data acquisition, cleaning, analysis, modeling, automation, visualization, dashboard development, web scraping, API use, quality control, and publication. Senior responsibilities add predictive modeling, machine learning, workflow supervision, project management, and establishing data-management best practices.

Manage and administer Mission Assurance databases while ensuring data integrity, security, availability, and performance. Support data collection, normalization, governance, quality control, repository integration, stewardship, and analytical workflow sustainment. Integrate assessment data with mission mapping, risk management, and criticality analysis to identify trends, vulnerabilities, dependencies, and enterprise-level risks. Apply advanced analytical techniques, including artificial intelligence and machine learning, to support Air Force mission assurance activities.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

Drive revenue growth across Federal Civilian agencies by acquiring new accounts, expanding existing contracts, managing sales cycles, building executive relationships, and achieving quotas. Develop sales strategies, forecasts, pipelines, and partner ecosystems with systems integrators and resellers. Present networking, security, AI, and data security solutions while communicating business value, ROI, and operational impact to technical and executive stakeholders.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead performance marketing data science initiatives focused on lead segmentation, bidding optimization, targeting, and marketing spend allocation. Develop and deploy production-ready machine learning systems, establish research and ML operations roadmaps, build monitoring frameworks, and identify high-impact opportunities. Partner with engineering, marketing, vendors, and executives while mentoring data scientists and machine learning engineers and promoting rigorous, maintainable, and reproducible practices.

Build and deploy AI agents, intelligent applications, scalable backend services, APIs, and full-stack solutions. Integrate large language models, AI services, data platforms, and external APIs into customer-focused products. Collaborate with engineering, product, and cross-functional teams while contributing to cloud-native applications, data pipelines, distributed systems, testing, deployment, and production operations.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Leads enterprise AI strategy and operations by building AI product portfolios, agentic workflows, copilots, intelligent applications, and human-AI experiences. Partners with executives, engineering, data science, security, and business teams to prioritize opportunities, establish roadmaps, redesign workflows, drive adoption, govern AI initiatives, and measure business value. Builds and leads AI product management teams while overseeing organizational change and cross-functional portfolio governance.

Drive new enterprise revenue and customer expansion by selling AI-powered SaaS solutions. Manage complex 6–12 month sales cycles, build executive relationships, develop value propositions, maintain pipeline accuracy, lead virtual account teams, and close high-value deals. Translate technical AI capabilities into measurable business outcomes, guide customer adoption, collaborate with marketing, product, and customer success teams, and exceed quarterly pipeline and revenue targets.

Lead product vision, strategy, discovery, and Agile delivery for insurance platforms. Partner with engineering, data science, design, QA, and insurance domain teams to prioritize opportunities, manage backlogs, evaluate build-versus-buy decisions, guide technical design, coordinate delivery, and measure outcomes. The role requires strong knowledge of insurance policy lifecycles, integrations, data modeling, pricing, underwriting, and AI-enabled workflows.

Leads product strategy, roadmap prioritization, AI and automation initiatives, client engagement, and cross-functional delivery for SPINS Intelligence and Portal. The role combines hands-on product management with PM team leadership, including writing user stories, defining acceptance criteria, triaging issues, reviewing sprint output, managing product economics, and developing business cases. Requires strong CPG, SaaS analytics, data product, AI/ML, and technical platform expertise.

Own Sophos EDR strategy, roadmap, technical product development, AI-powered experiences, and go-to-market execution. Translate customer needs, threat research, telemetry, competitive intelligence, and business goals into product priorities. Partner with engineering, security operations, threat research, marketing, sales, and customer success to deliver endpoint detection, investigation, threat hunting, response, reporting, and XDR/MDR upgrade capabilities while driving adoption, revenue, and customer outcomes.

Claims Counsel advises on auto insurance coverage, multi-state tort law, civil procedure, and litigation matters. Responsibilities include drafting coverage opinions, researching insurance laws, supporting claims policies and training, collaborating with legal and claims teams, conducting adjuster training, and drafting form letters and releases.

Lead the design and optimization of the VA VHA AI Education Hub, including its AI learning assistant, sandbox, integrations, analytics, and healthcare data models. Apply machine learning, synthetic data, privacy-preserving methods, and responsible AI practices in a secure federal healthcare environment. Collaborate with VA stakeholders and technical teams, document solutions, ensure governance and compliance, and present platform metrics and findings to leadership.

Architect and prototype scalable solutions for Twilio’s emerging technologies experimentation team. Lead AI, machine learning, and LLM-driven initiatives; guide technical direction; mentor engineers across the US and India; align prototypes with business goals; and ensure enterprise architecture, scalability, extensibility, and production readiness. The role requires extensive architecture or principal engineering experience, cloud expertise across AWS and Azure, full-stack development knowledge, database expertise, and strong technical leadership.

Owns the lifecycle of AI-powered analytics products supporting clinicians, from requirements and discovery through production and maintenance. Partners with data scientists, engineers, clinicians, and executives to define roadmaps, prioritize trade-offs, establish data contracts and SLAs, validate model results, track performance, and demonstrate ROI. Leads Agile scrum teams and drives cross-functional delivery in complex healthcare environments.

Own the AI product strategy and roadmap for HealthEdge’s HealthRules Payer platform. Identify and prioritize AI use cases across claims, member management, enrollment, benefits, and contracts; translate strategy into product requirements; and align product, engineering, data science, UX, marketing, and sales teams. Lead AI governance, regulatory compliance, customer presentations, go-to-market messaging, pilots, and feature commercialization while ensuring responsible AI use in healthcare payer workflows.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Own the design vision and execution for experimental AI-powered learning tools co-created with teachers and researchers. Design teacher- and student-facing products, create flows, wireframes, interaction designs, and functional prototypes, and facilitate collaboration across educators, researchers, engineers, and data scientists. Conduct usability testing and validate research hypotheses while navigating ambiguity, data-heavy workflows, and uncertain AI/ML-enabled features.

Supports defense IT portfolio modernization through requirements analysis, business process reengineering, enterprise and application architecture, systems mapping, technology evaluations, application consolidation, and technical gap analysis. Evaluates emerging AI and machine learning capabilities, commercial and government software, and program management tools. Provides technical support for IT governance, security reviews, audit compliance, BCAC processes, Oracle EBS, and phased modernization strategies.

Leads enterprise manufacturing AI, machine learning, and Industry 4.0 initiatives across multiple plants. Develops and deploys solutions for predictive maintenance, process and quality optimization, energy efficiency, throughput, and OEE improvement. Establishes scalable data and AI platforms, governance, and MLOps standards while integrating industrial data sources. Leads and mentors data science teams, prioritizes projects, allocates resources, partners with cross-functional manufacturing stakeholders, and presents strategic recommendations and business cases to executives.

Manage paid social campaigns and full-funnel strategies across Meta, LinkedIn, TikTok, Pinterest, Snapchat, and other paid channels. Oversee client accounts, analyze performance, identify growth opportunities, build client relationships, and collaborate with SEO, creative, and analytics teams. Contribute to thought leadership, coach associates, maintain quality standards, and explore automation, AI, and LLM search visibility initiatives.