Top Remote Machine Learning Jobs in Washington, DC

Lead digital transformation engagements by developing strategy, advising executives, and delivering end-to-end projects. Drive adoption of cloud, AI, data analytics, and emerging technologies while managing multidisciplinary teams, ensuring compliance, and measuring outcomes through KPIs.

Design, build, and deploy conversational AI solutions on the Kore.AI platform. Create and configure chatbots (intents, entities, dialog flows), integrate with back-end systems and REST APIs, and develop responsive user interfaces using ReactJS alongside UI/UX designers.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead go-to-market strategy for Magnet Forensics' security, incident response, and AI product portfolio. Influence executive, product, and sales stakeholders; translate technical AI/ML and forensic capabilities into messaging; develop buyer personas; create sales enablement and demand-generation content; evangelize products at events; partner with competitive intelligence and customer advocacy; mentor product marketing team members.

Design reusable software tools and subsystems, lead implementation and estimation, ensure systems integration and multi-platform compatibility, drive projects to completion, and perform feasibility analyses for future projects.

Lead architecture and engineering for AI-powered applications across backend, mobile, and desktop. Own reliability, observability, APIs, and model integrations. Grow and mentor a small senior applications team, drive production readiness, and make high-impact tradeoffs across latency, cost, security, and user experience to deliver reliable, low-latency AI-enabled workflows.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Lead end-to-end data science and AI projects: translate business problems, prepare large datasets, build and deploy predictive/prescriptive and generative AI models (including LLM fine-tuning and prompt engineering), communicate insights to stakeholders, and promote responsible, explainable AI practices across consulting engagements.

Enterprise sales role responsible for hunting new logos, growing revenue in an assigned Pacific Northwest territory, managing full sales cycle, building pipelines, collaborating with marketing and solutions architecture, and leveraging AI tools and technical knowledge of networking and security to close deals with executive stakeholders.

Lead complex transaction monitoring investigations to detect money laundering, terrorist financing, and fraud. Analyze large datasets and payment activity, coach analysts, review investigation quality, improve monitoring rules and processes, collaborate cross-functionally, and support regulatory reporting and audits.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Build and maintain full-stack features, data pipelines, and cloud infrastructure for large-scale ad management and analytics. Integrate with advertising platform APIs, apply ML/NLP for forecasting and recommendations, collaborate with product and marketing teams, and use AI coding tools to accelerate development.

Lead causal inference and measurement efforts for payments, build and evaluate ML/AI and LLM-based models, optimize fraud mitigation and loss strategies, simulate interventions, and communicate findings to stakeholders to drive product and risk decisions.

Lead Lean transformation initiatives and AI coordination to enhance process excellence across multiple business functions, coaching teams and ensuring integration with operational standards.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead and execute independent research programs on NLP and LLM safety, design and run experiments, secure funding, publish and present results, lead cross-functional teams, and develop evaluation tools and challenges to advance digital safety.

Provide legal support for commercialization and product development of an AI-powered ad tech platform: draft and negotiate commercial agreements, manage IP portfolio and complex IP litigation, advise on AI, data, and privacy matters, counsel product teams on compliance and IP protection, and develop automated legal workflows.

Own end-to-end compliance issue management for Lemonade's personal lines insurance products: identify, track, prioritize, remediate, and report issues; analyze data for root causes and trends; build remediation plans; recommend risk-based priorities to leadership; engage regulators; and develop AI/automation tools and cross-functional reporting to improve compliance processes.

Serve as primary post-sales strategic partner for largest enterprise clients, driving AI Agent adoption, ROI, optimization, governance, renewals, and cross-functional advocacy to turn customers into champions.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

Drive U.S. strategic growth by identifying, developing, and closing complex enterprise deals in the Databricks ecosystem. Build executive relationships, lead co-sell motions with partners, design account plans, and partner with Sales, Engineering, and Delivery to ensure successful execution and long-term value. Own CRM updates and relay market feedback to shape offerings and GTM strategy.

Lead strategy and execution to prevent, detect, and disrupt digital fraud, scams, and money mule activity. Build and mentor data science and analytics teams, develop ML predictive models, partner with product, cyber, vendors, and risk teams, and drive prevention-first controls, compliance, and operational efficiencies across payments, onboarding, and authentication channels.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.