Top AI & Machine Learning Jobs

Senior pre-sales leader who shapes AI solutions, leads discovery and executive engagements, develops architectures and proposals, validates feasibility with engineering teams, mentors junior consultants, and represents the company in events and thought leadership.

Build and deploy production AI at the edge: translate operational problems into AI requirements, design and optimize models (vision, language, multimodal, time-series), deploy containerized workloads across cloud and disconnected edge, implement monitoring and retraining pipelines, and collaborate with customers and engineering teams to move systems from prototype to resilient production.

Lead design and build of a greenfield LLM infrastructure and production LLM-backed features (RAG, streaming, tool use). Implement retrieval systems, embedding pipelines, model routing, instrumentation for failure modes, and own services end-to-end.

Lead end-to-end analytical design and validation for Signals, Forecasting, Simulation, Predictions, and Cohort Detection. Develop causal inference, time-series forecasting, survival/retention, and clustering methods; document assumptions and validation; partner with engineers to productionize models; ensure statistical rigor, significance correction, and trustworthy outputs that translate into clear product experiences.

Join as a Founding Engineer to design architecture, ship frontend and backend features, scale infrastructure for large-scale voice AI calls, improve conversation quality, interact with customers, and contribute to research and product vision.

Lead design, development, and delivery of production-ready AI capabilities and platforms. Provide hands-on technical leadership, mentor AI engineers, drive MLOps and model lifecycle practices, evaluate and integrate LLMs and AI frameworks, and collaborate cross-functionally to ensure secure, scalable, and compliant AI solutions.

Build and ship production-grade AI agents and models to automate insurance workflows, integrate deeply with carrier APIs, and take end-to-end ownership of projects from prototyping to deployment.

Work directly with SMB clients to discover operational inefficiencies and design incremental AI and automation solutions deliverable in 30–90 days. Lead client workshops, define scopes and SOWs, quantify ROI, build repeatable service offerings, evaluate emerging tools, and present business-focused recommendations to leadership.

Design and optimize a low-level AI inference serving stack: customize open-source frameworks, build model partitioning/scheduling, integrate with proprietary accelerators, profile and optimize across Python orchestration to C++ kernels and drivers, and enable PyTorch-native deployment tooling.

Lead design and implementation of cloud-first, AI-integrated full-stack applications on GCP. Drive rapid prototyping and MVPs, mentor developers, define architecture, maintain CI/CD pipelines, and collaborate cross-functionally to deliver production-ready solutions.