Top Tech Jobs & Startup Jobs

Lead the rapid development and release of AI safety and security benchmarks. Own evaluation taxonomies, harnesses, quality standards, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelance subject-matter experts. The role also requires reviewing research, engaging with frontier labs, presenting findings, and attending industry conferences.

Lead the development and release of AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, verification, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelancers. The role also requires staying current with AI safety research, maintaining lab relationships, presenting work to clients, and attending conferences.

Lead the development and release of frontier AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelance subject-matter experts. Conduct hands-on evaluation review, maintain ecosystem relationships, present research to clients, and attend conferences.

Principal-level hands-on engineer embedded in a product pod to drive 0-to-1 innovation. Responsibilities include architecting, coding, and launching greenfield products; creating demos and proofs of concept; leading high-stakes technical client discussions; shaping roadmaps and integration specifications; identifying automation opportunities; and resolving critical engineering bottlenecks. The role requires exceptional system design, modern AI expertise, commercial judgment, client presence, autonomy, and experience shipping complex software from scratch.

Serve as the senior technical front line for frontier AI lab clients in the Bay Area. Lead technical discovery, RFPs, solution scoping, client meetings, events, and technical discussions with engineering and research teams. Build the Valley AI and security community, represent the company publicly, translate market signals into research and product strategy, and help establish the company’s regional presence. Partner with sales on technical wins while influencing AI security research, product direction, and local hiring.

Lead post-training evaluation, red-teaming, and reinforcement-learning gym audits for open-weight models. Build benchmarking and evaluation pipelines for LLM security threats such as indirect prompt injection, analyze reward diagnostics and rollout traces, audit agentic environments, produce evaluation cards, and integrate Dockerized environments into distributed training frameworks. The role requires expertise in RL training, AI security, PyTorch, containerization, verifiers, reward shaping, and agentic tool-use workflows.

Own full-cycle global recruitment for specialized technical roles, partnering with executives and hiring managers across regions. Source candidates, optimize AI-driven recruiting workflows, analyze hiring KPIs, support employer branding, and improve hiring-to-onboarding outcomes. The role requires strong communication, data analysis, stakeholder management, international hiring experience, and proficiency with ATS and modern sourcing tools in a fast-paced technology environment.

Lead and grow a multidisciplinary Data Science engineering team building real-time content moderation, GenAI safety and red-teaming systems, and Databricks-based data and MLOps platforms. Set technical direction, own delivery and quality, mentor and hire engineers, review designs, and drive reliability, observability, CI/CD, cost, latency, and production ML excellence across Python, Rust, Spark, AWS, Kubernetes, and model-serving infrastructure.

Conduct Android malware research, reverse engineering, and static and dynamic analysis. Detect emerging threats and attack vectors, analyze applications for malicious behavior, write detection rules, develop automation, and document findings for threat intelligence reports. Collaborate across teams and share technical knowledge. Requires at least three years of relevant research, reverse engineering, or low-level development experience, programming proficiency, and familiarity with malware analysis tools.

Research and analyze fraud detection mechanisms, abuse vectors, platform vulnerabilities, and emerging fraud tactics across web, mobile, social, forum, and dark web environments. Conduct OSINT and WEBINT investigations, validate abuse scenarios, operate technical research infrastructure, analyze datasets and telemetry, automate workflows, monitor third-party channels, and deliver actionable intelligence and mitigation recommendations.