Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Scope and size complex AI data projects during pre-sales, drive account growth with strategic customers, lead implementations and integrations, improve delivery reliability, and translate recurring customer needs into product requirements.

Own Mercor's first mobile app from concept to launch and iteration. Define roadmap for experts to apply, track contracts, and submit assessments on mobile. Manage end-to-end lifecycle including specs/PRDs, release management, app store operations, analytics and instrumentation, post-launch growth, and user research. Align product decisions to business outcomes and build scrappy MVPs or dashboards to validate direction.

Build and deploy ranking, matching, recommendation, and allocation ML systems for a global talent marketplace. Work across retrieval, scoring, inference (real-time and batch), feedback loops, and experimentation to optimize long-term hiring outcomes under marketplace constraints.

Own major product areas to convert human expertise into training data and tooling for AI. Conduct user research, write specs, build dashboards/MVPs, partner with engineering/research/ops/design, and drive product strategy from conception to execution.

Build end-to-end RL environments and verifiers from enterprise data: ship workflow extraction and grading models, automate task-refinement pipelines, platformize sandbox app clones with real data, deliver data to customers, and scale environment production while preserving high fidelity.

Design, implement, and operate large-scale evaluation and benchmarking pipelines for LLMs. Build rubrics, automated scorers, dashboards, and failure-analysis workflows to quantify model errors, guide data curation, and inform training and reward-design decisions. Collaborate with researchers, applied-AI teams, and data producers to prioritize and scale evaluations aligned with product and research goals.

The Fullstack Software Engineer will develop and manage the Studio platform's frontend and backend, ensuring reliable data workflows and user-friendly interfaces. Responsibilities include leading engineering best practices, collaborating on technical solutions, and shipping impactful features for AI data generation and delivery.

Own end-to-end high-value code-data programs: evaluate frontier coding models, design human/synthetic/model-in-the-loop pipelines, run delivery and QA, manage expert labeling teams, and act as primary customer contact for AI labs.

Lead design and implementation of Mercor's code search and retrieval systems: hybrid dense-code embeddings plus lexical (BM25) retrieval, candidate generation, ranking/re-ranking, model routing, query translation from natural language, indexing pipelines, evaluation/A-B testing, and technical leadership to evolve embeddings and search quality safely at scale.

The Enterprise AI Lead will manage enterprise customer relationships, drive commercial strategy, and lead cross-functional initiatives in AI-driven solutions.