Top AI & Machine Learning Jobs

The AI Full Stack Engineer will design and build AI-powered healthcare products, oversee backend and frontend development, and influence technical direction in a collaborative, fast-paced environment.

Lead retention and churn efforts by building survival and lifecycle-state models, classifying churn reasons, creating personalized win-back and next-best-action interventions, optimizing offers/promos, designing uplift experiments, and owning production model lifecycle, monitoring, and MLOps across Product, CRM, Marketing, and Engineering.

Lead the design and implementation of therapy algorithms, optimizing patient outcomes through data analysis and collaboration with cross-functional teams.

Lead a 3–4 month customer engagement to design, implement, and deploy production-ready data and agentic applications on the Nextdata OS. Responsibilities include data integration, modeling, pipelines, infrastructure, APIs, semantic interfaces, and building user-facing agent workflows (LangChain/LangGraph), ensuring governance, access controls, and production reliability.

Design, build, and iterate AI agents, copilots, and assistant experiences using Microsoft Copilot Studio, Azure AI, and Power Platform. Configure knowledge sources, partner with stakeholders to prototype solutions, evaluate agent performance, refine prompts and grounding, and document and package reusable templates toward production readiness.

The role involves designing, developing, and maintaining AI/ML tools, particularly focusing on LLM orchestration frameworks and data optimization, while collaborating with mission stakeholders and supporting security assessments.

Lead design and delivery of Microsoft AI solutions across Azure AI, Azure OpenAI, Copilot, M365, Teams, and Dynamics 365. Translate business problems into secure, scalable AI architectures, support presales, create solution artifacts, guide deployments, and ensure transition to managed services while contributing reusable IP and governance practices.

Design and deliver derivatives hedging and financing solutions by building pricing, risk, and scenario models; develop data pipelines and analytics platforms; create AI-driven agentic workflows and knowledge tools; integrate AI with internal systems for real-time analytics; support front-office OTC derivatives, client pitches, and proprietary platform development.

As an AI/ML Presales Solutions Architect, you will engage with clients to identify problems, create feasible AI solutions, and partner with sales to ensure project delivery aligns with capabilities. You will leverage your extensive experience in AI and cloud platforms to shape presentations and technical discussions with clients.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.