Top Tech Jobs & Startup Jobs in NYC, NY

Manage press and podcast outreach logistics, produce and distribute the Epoch Brief newsletter, draft short-form social and website copy, implement paid ad campaigns, update evergreen website content, monitor media contacts and social replies, and grow into longer-form drafting and editing in collaboration with the Lead Editor.

Open call for expressions of interest across research, operations, engineering, data, and communications. Epoch AI is fully remote, hires in many countries, prefers full-time, and may require meetings during UTC-8 to UTC+1. Submit interest to be contacted for suitable openings.

Lead and conduct research projects analyzing AI capabilities, datacenters, supply chains, benchmarks, and trends. Produce datasets, benchmarks, reports, and forecasts; evaluate technical claims; collaborate across teams and communicate results clearly. Drive new research directions and prototype evaluation methods.

Contract data scientist to remotely gather, extract, and analyze technical information about AI models, benchmarks, data centers, and companies. Tasks include reading ML papers, tracking leaderboards, processing satellite images/permits, compiling infrastructure details, and producing data insights for research and policy. Part-time (10–30 hrs/week), flexible schedule with occasional Pacific Time meetings.

Lead Recruiting, HR, and Events for rapid growth from ~30 to ~70 people. Build and scale hiring systems, onboarding, benefits, compliance (including visas), performance processes, and the events calendar. Manage a team of ~5, advise leadership on org design, report hiring metrics, and ensure employee support and culture as the organization scales.

Analyze and critique new AI benchmarks every two weeks, evaluate methodologies and implications for capabilities, publish and maintain public-facing reports, and examine benchmark tasks and data in detail (using coding agents to assist while retaining independent judgment).

Design and maintain a realistic benchmark suite of open-ended office tasks, create grading rubrics, run and analyze frontier AI models, produce public-facing evaluations and visualizations, and improve/automate evaluation workflows.

Run, maintain, and expand an AI benchmarking infrastructure: implement and integrate benchmarks (primarily using the Inspect library), develop new benchmarks and prototypes, collaborate with researchers and engineers, and ensure evaluation outputs are accurate and integrated into research products.