Top Senior Machine Learning Jobs in Washington, DC

Design and lead the technical strategy for search across Vannevar’s products. Build and improve full-text, vector, and LLM-powered retrieval systems, optimizing latency, relevance, index quality, freshness, and performance. Collaborate with ML, product, design, and mission strategy teams to translate user needs into search innovations. Apply expertise in information retrieval, NLP, machine learning, indexing, ranking, query parsing, tokenization, vector search, and evaluation frameworks.

Lead Runpod’s Americas sales organization and revenue number across new business, expansion, and renewals. Manage and coach Account Executives and Account Managers, oversee forecasting and pipeline, lead complex enterprise deals and contract negotiations, build regional go-to-market strategy and sales playbooks, and convert product-led demand into revenue. Partner with Marketing, Product, Legal, and Finance while improving sales efficiency through AI and developing a remote-first team.

Develops and validates machine learning and statistical models for anti-money laundering, transaction monitoring, customer screening, and risk rating. The role evaluates AML data quality, integrates vendor solutions, maintains governance and regulatory documentation, leads model lifecycle quality control, and reports performance through management dashboards. It also supports AML risk assessments, audits, regulatory examinations, and cross-functional stakeholder coordination.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Leads business analysis and discovery for mortgage technology initiatives, partnering with operations and technology teams to improve loan origination workflows. Identifies automation and AI opportunities, evaluates business cases, translates mortgage requirements into user stories and functional solutions, and supports implementation, testing, training, and adoption. Requires substantial business analysis and mortgage industry experience, especially in non-Agency lending environments.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Designs production-ready AI architectures for enterprise customer-experience use cases. Leads presales discovery, demonstrations, prototypes, pilots, integrations, and solution validation involving LLMs, RAG, agentic AI, workflows, enterprise data, and cloud ecosystems. Establishes evaluation, observability, governance, security, scalability, latency, and cost strategies while influencing CIO and CTO stakeholders. Partners with sales, Professional Services, Product Management, and Engineering, and develops reusable enablement assets to scale field AI expertise.

Provides legal counsel on U.S. privacy, cybersecurity, data management, software development, artificial intelligence, and incident response. Advises cross-functional teams, assesses regulatory and business risks, supports privacy impact assessments, negotiates privacy and cybersecurity provisions, and assists with compliance and legal programs. Requires strong legal research, negotiation, communication, judgment, and knowledge of financial services operations, privacy laws, cybersecurity regulations, and emerging AI technologies.

Develops, edits, and maintains technical documentation, user guides, procedures, specifications, training materials, style guides, and executive communications. Translates complex technology concepts for technical and non-technical audiences while collaborating with engineering teams, stakeholders, and leadership. Supports information architecture, documentation repositories, application modernization, technical roadmaps, and enterprise technology initiatives in an onsite federal environment.

Administers hybrid Azure, AWS, and on-premises infrastructure, including servers, virtualization, networking, storage, identity, containers, and security. Develops automation with PowerShell, Python, and Terraform; manages Kubernetes and Docker environments; implements monitoring, AIOps, disaster recovery, and business continuity. Supports DevOps and DevSecOps practices, CI/CD pipelines, machine-learning-enabled infrastructure optimization, and security compliance while mentoring junior staff.

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.

Own and grow a Southeast or Mid-Atlantic commercial territory targeting companies with 500–2,500 employees. Responsibilities include prospecting, pipeline development, new business acquisition, upselling and cross-selling, multi-product deal closure, forecasting, territory management, executive presentations, negotiation, industry events, and collaboration with internal and channel teams. The role requires communicating cybersecurity and identity-access solutions to business leaders while consistently achieving sales quotas.

Designs and implements AI solution architectures and strategies addressing client business needs and ethical considerations. Develops innovative solutions using AI, machine learning, deep learning, computer vision, NLP, and agentic AI. Leads technology assessments, evaluates alternatives, develops requirements, conducts independent research, translates complex technical topics for broad audiences, and mentors team members. Requires Python programming, modern software design knowledge, a STEM degree, and Secret clearance eligibility.

Develops strategic relationships and revenue growth with universities and higher-education research institutions. Owns the complete sales cycle, from prospecting and discovery through negotiation and closing, while meeting quotas and forecasting revenue. Creates territory and account plans, translates complex software and computing requirements into NVIDIA solutions, and collaborates with solution architects, product teams, developer relations, business units, and channel partners. Requires consultative technology sales expertise and understanding of AI, accelerated computing, and research environments.

Designs, develops, and operationalizes machine learning models and advanced analytics for a 24x7 Security Operations Center. Analyzes security telemetry, builds data pipelines and feature engineering workflows, integrates analytics with SOC tools using Docker and Kubernetes, and applies threat frameworks such as MITRE ATT&CK. Provides technical leadership, mentors analytics personnel, collaborates with SOC analysts and engineers, and delivers documentation, performance metrics, and leadership briefings.

Develops advanced data analysis, visualization methodologies, intelligence support packages, and machine learning models for a federal client. Processes disparate data, identifies trends and relationships, delivers infographics and stakeholder briefings, documents technical solutions, and supports architectural reviews. The role requires Python-based data science experience, Agile development familiarity, strong communication skills, a bachelor’s degree, and an active Top Secret/SCI clearance.

Develop and evaluate supervised and unsupervised machine learning and AI models for a federal law enforcement data program. Apply NLP to extract and enrich entities from unstructured data, prepare structured and unstructured datasets, create visualizations, and communicate findings to technical and non-technical stakeholders. Collaborate with an Agile delivery team on enterprise data analytics and mission-focused modeling.

Develop and maintain capacity management plans for hybrid virtual private cloud and global IT infrastructure. Analyze utilization and performance, forecast resource needs, define capacity metrics and thresholds, monitor trends, identify risks, support budgeting, and tune infrastructure in coordination with change management. Apply advanced analytics and machine learning to predict resource requirements and prevent performance degradation.

Lead corporate communications strategy and execution: own product and model launches, media and executive communications, narratives, social presence, and major company moments. Translate technical research and product advances into compelling stories for developers, enterprise buyers, partners, and analysts. Partner cross-functionally with CEO, CMO, product, brand, and demand gen to build credibility and influence in the voice AI ecosystem.

Own and execute multi-year strategic partnerships with a hyperscaler and an AI lab, aligning technical integrations, commercial motions, and joint go-to-market plans. Coordinate cross-functional teams, run operational cadences, track measurable outcomes (pipeline, ARR, integrations), and represent partnerships to executives while driving hands-on execution and follow-through.

Lead forensic technology engagements by designing and deploying machine learning models, statistical algorithms, and data pipelines for digital investigations and electronic discovery. Collaborate with clients to define goals, analyze cloud and enterprise data, develop reusable automation components, communicate findings to executive audiences, and deliver training. The role also involves managing people on high-profile consulting engagements and providing client-facing technical leadership.

Provides strategic legal counsel on product, intellectual property, and AI matters. Oversees the worldwide IP portfolio, develops IP strategy, manages invention disclosures and patent prosecution, advises business and product teams on global IP law and compliance, supports commercial agreement negotiations, and advances product legal strategy. Requires substantial in-house and law-firm experience, a California law license, and expertise in AI, machine learning, and generative AI technologies.

Leads complex enterprise transformation workstreams, developing workplans, business recommendations, quantitative insights, executive communications, and action plans. Partners with senior stakeholders to design and implement large-scale healthcare strategy and operational initiatives. The role requires structured problem solving, program management, cross-functional collaboration, healthcare or management consulting experience, and the ability to influence executive decision-makers. Occasional travel to Humana offices may be required.

Builds dashboards, applications, automations, ETL integrations, predictive risk models, and AI/ML solutions for unstructured data. Performs data normalization, visualization, business intelligence analysis, and risk assessment improvement. Recommends data storage and integration solutions, creates Power BI documentation, and applies SQL, R, Python, and other data science tools to federal systems and public-sector projects.

Manages project controls for major nuclear energy projects, overseeing planning, scheduling, budgets, cost management, risk mitigation, earned value management, reporting, change control, and continuous process improvement. Leads and mentors project controls professionals, ensures consistent methodology application, and communicates project performance to stakeholders and senior leadership. The role also encourages using AI, machine learning, and advanced analytics to improve forecasting, scheduling, risk analysis, and reporting.