Top Tech Jobs & Startup Jobs

Conduct research on frontier AI systems and develop datasets, experiments, prototypes, tooling, evaluation frameworks, and reinforcement learning environments. Investigate synthetic and agentic data generation, post-training, model understanding, benchmarks, and evaluation. Collaborate with research, engineering, product, and operations teams to translate findings into scalable AI applications, while contributing to technical publications, open-source work, mentorship, and the broader AI research community.

Conduct original research to develop frontier STEM benchmarks, evaluations, synthetic data methods, hallucination and reliability techniques, and agentic science workflows. Responsibilities include identifying research gaps, designing experiments, building evaluation pipelines, validating results, constructing benchmarks, and publishing findings. The role requires strong knowledge of modern LLMs, scientific judgment, quantitative reasoning, Python, technical writing, and independent research execution. This is an in-office position five days per week in San Francisco, Palo Alto, or Seattle.

Conduct frontier AI research and build research-grade datasets, prototypes, tooling, reinforcement learning environments, benchmarks, and evaluation frameworks. Design rigorous experiments, train and evaluate models, investigate synthetic and agentic data generation, and translate findings into scalable products. Collaborate with research, engineering, product, and operations teams, communicate technical insights, contribute to publications and open-source work, and mentor peers. This is a fully onsite role based in San Francisco, Palo Alto, or Seattle.

Conduct original research to evaluate, train, and improve frontier AI systems. Responsibilities include developing STEM benchmarks, synthetic data methods, reliability and hallucination evaluations, verification techniques, and agentic science workflows. The role involves identifying research gaps, designing rigorous experiments, building evaluation pipelines, publishing findings, and proposing new research directions across reasoning, AI evaluation, data generation, and AI-for-science.

Conduct original research to evaluate, train, and improve frontier AI systems. Design benchmarks, synthetic-data methods, reliability and hallucination evaluations, verification techniques, and agentic science workflows. Identify research gaps, formulate hypotheses, build experiments and evaluation pipelines, publish findings, and develop new research directions across STEM and AI. The role requires strong Python skills, quantitative reasoning, technical writing, and expertise with modern LLMs.

Conduct frontier AI research and build research-grade datasets, prototypes, tooling, reinforcement learning environments, benchmarks, and evaluation frameworks. Investigate synthetic and agentic data generation, post-training, model understanding, and model capabilities. Design rigorous experiments, analyze results, and translate findings into scalable products and AI systems while collaborating across research, engineering, product, and operations teams.

Build and deploy production generative AI systems for enterprise clients, from problem discovery and architecture through implementation, deployment, and measurable business impact. Responsibilities include multi-agent workflows, RAG, tool use, data pipelines, integrations, distributed systems, security, reliability, observability, scalability, latency, and cost optimization. The role requires direct client collaboration, stakeholder communication, technical leadership, and completion of an intensive eight-week applied AI training placement.

Leads information security governance, compliance, data protection, privacy, enterprise risk, third-party risk, and customer trust programs. Owns SOC 2 and ISO 27001 certifications, audits, security policies, data security strategy, GDPR and CCPA/CPRA compliance, and executive risk reporting. Builds and manages a team spanning GRC, privacy, and risk while partnering with engineering, legal, product, sales, and leadership.

Lead complex, cross-functional security programs from planning through delivery. Responsibilities include managing compliance certifications, remediation initiatives, incident-driven improvements, and security rollouts; defining milestones, dependencies, risks, and success metrics; coordinating security, engineering, GRC, IT, legal, product, and executive stakeholders; and improving security organization planning, roadmapping, prioritization, and reporting.

Investigate fraud and insider-threat cases from initial signal through resolution. Gather and analyze logs, transactions, behavioral signals, and other evidence; triage alerts; reconstruct events; document findings objectively; maintain evidence chain of custody; and collaborate with Detection & Response, Legal, and HR. The role also contributes to investigation playbooks, detection improvements, and fraud and insider-risk prevention.