Top AI & Machine Learning Jobs

Design, implement, and operationalize machine learning and analytics software for production environments. Build data pipelines, deploy tools, monitor system performance, and productize research into reliable, containerized solutions while collaborating with researchers and customers.

Lead design, develop, integrate, test, and demonstrate autonomy and multi-agent algorithms and backend software for unmanned systems. Provide technical leadership, mentor engineers, drive software architecture and best practices, and support DevSecOps/CI-CD pipelines from prototype to deployed system.

Operationalize and productionize machine learning and statistical algorithms: build data pipelines, deploy and monitor production systems, containerize and orchestrate services, collaborate with researchers and customers, and implement software standards to ensure robust, reliable operational analytics for national security use cases.

Lead design and deployment of production-grade ML systems (ranking, retrieval, LLMs). Drive architecture decisions, run experiments and evaluations, build scalable feature pipelines and monitoring, mentor engineers, and collaborate cross-functionally to integrate AI into products and scale ML capabilities.

Lead and grow a high-performing ML team to design and deliver end-to-end AI features for DevAI products. Drive LLM integration, prompt engineering, technical strategy, project delivery, stakeholder alignment, and process optimization while mentoring engineers and managing performance.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

Design, develop, and deploy AI-native software that converts large-scale geospatial data into actionable intelligence. Build multi-agent workflows and integrate LLMs (GPT-4, Claude, Gemini) for contextual analysis and autonomous reasoning. Engineer agents with tool use, iterative self-refinement, and feedback loops; develop data ingestion and transformation layers; ensure secure, scalable cloud integrations; and deploy/operate systems in production using containerization, orchestration, and CI/CD.

Lead quality assurance for geospatial imagery annotation across EO, SAR, and commercial sources. Mentor junior annotators, validate bounding-box/segmentation/point labels, identify systemic issues, write SOPs, and improve annotation tools and pipelines to support downstream AI/ML model needs.

Design, build, and own production AI agents and automations for marketing. Integrate and instrument the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), implement predictive scoring and personalization, monitor systems for reliability, and collaborate with marketing, RevOps, and sales to translate problems into deployable software.

Use AI coding agents to build end-to-end applications, automations, and basic agents. Translate customer needs into deployed solutions, instrument and iterate on outcomes, evaluate AI output for security/privacy/quality, engage with customers, and document prompts and patterns.

Lead end-to-end product builds by orchestrating AI coding agents to create applications, automations, and basic agents. Translate customer problems into deployable solutions, instrument usage and outcomes, evaluate AI output for security/privacy/quality, engage with customers to find automation opportunities, and document prompts, patterns, and approaches for the team.

Use AI coding agents to build end-to-end applications, automations, and basic agents. Translate customer needs into deployed solutions, instrument and iterate on outcomes, evaluate AI output for security/privacy/quality, engage with customers, and document prompts and patterns for the team.

Lead design and implementation of LLM-powered conversational financial interfaces. Architect secure, zero-trust orchestration (tools, chains, policy layers), own full-stack services and data pipelines, partner with product, and mentor global teams to deliver production-grade intelligent customer experiences.

Build end-to-end agentic AI systems for healthcare customers: discover needs, architect and code solutions, onboard customers, monitor and iterate production systems, mentor junior builders, and collaborate with stakeholders to deliver reliable, AI-native patient workflows.

Build and scale Klaviyo's AI-native Customer Agent platform across frontend and backend. Design conversational experiences, retrieval and orchestration systems, integrations, observability, and deployment. Drive architecture, mentor engineers, ensure reliability, and ship high-quality, scalable AI-driven customer engagement features.

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