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

Own the full lifecycle marketing program for a contributor workforce, including onboarding, activation, engagement, retention, and reactivation. Lead email strategy, segmentation, deliverability, testing, copywriting, and performance analysis. Run paid marketing experiments, productize marketing playbooks, and apply UX sensibility to communications. Collaborate with product, design, operations, and growth teams on positioning, messaging, launches, and platform improvements.

Design scalable human-data collection systems for AI model post-training, including task frameworks, data workflows, quality assurance, evaluation datasets, and delivery pipelines. Partner with engineering and product teams to improve throughput and reliability while preserving data quality. Translate collection and quality patterns into insights that improve project design, client deliverables, and product development.

Oversee end-to-end product operations, coordinate with product and engineering teams, track performance metrics, resolve operational roadblocks, manage product communications, and use data-driven insights to improve delivery and operational efficiency.

Conduct hands-on research with frontier AI labs to evaluate model behavior, identify failure modes, and design interventions that improve reliability. Responsibilities include designing evaluations, building data pipelines and fine-tuning workflows, collaborating with internal and external stakeholders, and addressing challenges involving long-context reasoning, tool use, and real-time feedback loops.

Research data strategies for large language model development, including designing data slices to identify model failure modes, modeling annotator behavior, and optimizing instruction clarity and reward-signal reliability. Develop metrics and evaluation frameworks to assess dataset quality, diversity, alignment impact, and downstream model performance. Collaborate with AI research teams and test data-centric methodologies in production environments.

Design and govern reinforcement learning environments, including modular APIs, curricula, reward and termination schemas, quality standards, telemetry, and evaluation suites. Build robust simulations of real-world tasks, synthetic data generators, and multi-agent ecosystems while mitigating reward hacking, mode collapse, and exploitable loopholes. Partner with research and engineering teams to create deterministic, observable, scalable environments and maintain reproducible, high-quality training signals.

Design and build core fullstack systems powering Surge’s AI platform. Own frontend product decisions, backend architecture, and high-impact workflows for data collection, labeling, and evaluation. Ship scalable, reliable, intuitive tools while making autonomous technical decisions, collaborating with engineering and machine learning leaders, and maintaining high standards for usability, performance, and maintainability.

Manages strategic client accounts for an AI data platform, serving as the primary customer contact and trusted advisor. Oversees data projects, SLAs, quality, and deliverables while coordinating engineering, operations, and project teams. Builds strong client relationships, addresses concerns, translates AI and NLP requirements into actionable plans, and ensures solutions meet customer goals.

Lead finance-focused AI training, evaluation, and data programs across financial analysis, equity research, credit assessment, regulatory compliance, and quantitative modeling. Serve as the finance subject-matter expert, establish quality frameworks, coordinate cross-functional teams, manage timelines, and translate financial expertise for AI/ML teams and financial-services clients.

Lead customer-centric product development and strategic initiatives for an AI platform. Responsibilities include understanding customer pain points, overseeing product and operations execution, managing accounts, building scalable systems and processes, coordinating with engineering, analyzing performance data, and driving product insights through market and competitive research.