"human preference model" Jobs
2265 open tech roles matching “human preference model”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Python, AI/ML, SQL. Every listing is re-checked daily and closed roles are removed.
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Join Sarvam as an HR Business Partner to shape HR strategy and operations in a fast-paced AI company.
Support cyber product policy work at Anthropic, ensuring compliance with usage policies and safety standards.
Join Neuralink as a Machine Learning Engineer Intern to develop neural decoders for advanced Brain-Computer Interfaces.
Lead Claude Corps, a $150M early career program, to enhance economic mobility through AI partnerships.
Drive the success of Productions at ElevenLabs, managing language teams and ensuring high-quality audio content creation.
Lead integrated marketing campaigns for Anthropic's Enterprise business, driving demand and adoption across strategic customer segments.
Join Anthropic as a senior Program Manager to lead communications during critical moments and ensure clarity under pressure.
Lead a team managing critical AI data projects at Handshake, ensuring high-quality delivery and operational excellence.
Lead the Agents Experience team at Asana to define the collaboration between humans and AI agents in a hybrid work environment.
Lead the Influence Operations & Surveillance team to counter misuse of AI systems in a rapidly evolving threat landscape.
Join Arena as an Applied AI Engineer to integrate AI models and build solutions for cutting-edge AI teams.
Join Hebbia AI as a Backend Engineer to build scalable solutions for advanced AI-driven investment analysis.
Join Anthropic's Inference team to design and maintain distributed systems that serve AI models to millions of users worldwide.
Lead the execution of Asana's compensation programs while ensuring equity and competitive salary structures in a hybrid work environment.
Drive the clinical AI research agenda for Anthropic's global health work, ensuring AI tools are safe and effective in low-resource settings.