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

Own the full enterprise B2B SaaS sales cycle, from prospecting and discovery through negotiation, closing, and account expansion. Build relationships with senior executives, manage complex multi-stakeholder deals, develop business cases, maintain pipeline and CRM accuracy, and contribute to scalable sales playbooks and go-to-market strategies. Collaborate with founders, Product, Marketing, and revenue leaders in a fast-paced, early-stage environment.

Own the full enterprise sales cycle, from prospecting and discovery through negotiation, closing, and account expansion. Build relationships with senior executives, manage complex multi-stakeholder deals, develop business cases, maintain pipeline and CRM accuracy, and contribute to sales playbooks and go-to-market strategy. Collaborate with founders, Product, Marketing, and revenue leaders in a fast-paced early-stage environment.

Build and deploy AI-driven web applications across frontend and backend. Design scalable backend systems, responsive TypeScript frontends, ETL pipelines, and integrate ML models into production. Work with cloud platforms, containerization, APIs, automated testing, and cross-functional teams to deliver robust, high-performance solutions.

Evaluate and improve the safety, security, and robustness of large language models. Responsibilities include designing jailbreak, prompt injection, adversarial, and tool-use abuse tests; developing regression suites and evaluation frameworks; identifying vulnerabilities; translating findings into safety recommendations; and documenting methodologies and results for technical and non-technical stakeholders.

Red team conversational AI models and agents by probing jailbreaks, prompt injections, misuse cases, bias, and multi-turn manipulation. Annotate failures, classify vulnerabilities, apply testing frameworks and benchmarks, and produce reproducible reports, datasets, and attack cases. The role requires native English and Finnish fluency, prior AI or cybersecurity red teaming experience, strong communication, structured analysis, and adaptability across projects.

Develop data-driven solutions to complex real-world problems using data science, machine learning, statistical modeling, and analytical reasoning. Candidates should currently work in a technical data science or machine learning role at a leading technology company, hold a quantitative undergraduate degree from a top-ranked university, and reside and work in an eligible English-speaking country.

Design, develop, test, and maintain scalable software applications and systems. Write high-quality code, solve complex technical problems, collaborate with product and engineering teams, participate in code reviews and debugging, contribute to system architecture, and improve engineering processes. The role requires strong software fundamentals, production-scale experience, and familiarity with Databricks, distributed systems, and cloud infrastructure.

Reviews and compares AI chatbot responses using predefined criteria for accuracy, relevance, completeness, clarity, consistency, and quality. Documents evaluation guidelines, analyzes workflows and data, identifies recurring issues, prepares reports, tracks quality metrics, and collaborates with project teams. This fully remote, 16-week contract requires 8 hours per day, five days per week, with Pacific Time overlap and possible weekend work.

Evaluate educational AI conversations and generated responses for accuracy, relevance, completeness, clarity, and logic. Conduct research and fact-checking, synthesize information, annotate errors, provide evidence-based feedback, and create training data examples to improve AI models. The role requires reviewing genuine Gemini conversation history, submitting an exported JSON file, and working full-time remotely for a 16-week contract with PST overlap.

Design and validate complex engineering simulation problems for training and evaluating AI models and coding agents. Develop Python-based simulation workflows, automated tests, reference solutions, and grading systems across electrical, mechanical, and aerospace domains. Analyze AI execution logs and failure modes, validate physical plausibility and numerical convergence, refine benchmarks, and collaborate with engineering and AI research teams. This remote contractor role requires approximately 40 hours weekly, Pacific Time overlap, and weekend on-call availability.