Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.

Design, build, and scale production-grade AI applications and agent-based systems. Lead technical customer engagements, create reusable solution accelerators, drive adoption, ensure production readiness (security, scalability, observability), and influence product roadmap while scaling field capabilities and delivery patterns.

Serve as the primary delivery lead for strategic customers, driving post-sales adoption and value across Microsoft cloud platforms. Manage stakeholder relationships, orchestrate delivery resources, track consumption and adoption, resolve blockers, run program reviews, and align technical solutions (Azure, Modern Work, Dynamics) to customer business outcomes. Use Microsoft delivery methodologies and collaborate with partners and account teams.

Lead end-to-end data science projects: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, operationalize models at scale, run experiments, drive ethics/privacy, partner with customers and teams, and coach cross-disciplinary colleagues.

Lead product and program analytics for Microsoft skilling experiences: design learner journey/funnel analyses, define success metrics, run experiments and causal analyses, build proficiency/competency models, shape telemetry and scalable reporting, recommend content and curriculum improvements, and mentor other data scientists to drive product decisions and learning outcomes.

Lead definition and ownership of core growth data models and metrics, build certified data products and agentic features (NL access, anomaly detection, reporting), align teams on shared schemas and definitions, instrument funnels, and drive adoption and retirement of duplicate reports.

Manage execution of SPEAR threat intelligence operations: prioritize and track RFI workflows, translate business needs into technical specifications, coordinate analysts and engineers, ensure data quality and security, develop reporting/dashboards and SOPs, and communicate with stakeholders to drive timely intelligence delivery.

Lead technical pre-sales engagements for Microsoft cloud database and analytics products. Deliver PoCs, demos, hackathons, and architecture workshops; design secure, scalable solutions; resolve technical blockers; collaborate with engineering; and evangelize Fabric, Databricks, Purview and Azure database technologies to accelerate customer migrations and adoption.

Develop and iterate post-training methods for large language models: drive data collection, build evaluations, design experiments, and apply reward modeling and RL techniques to improve model capabilities and deployment.

Lead and scale teams building offensive and defensive AI agents and the ML, data, and safety systems that power them. Drive strategy, production-grade engineering, safety and governance, cross-team collaboration, and hiring/leadership development to deliver secure, reliable agentic security capabilities for customers.