AI Lab Research Engineer (AI)

TL;DR

AI Lab Research Engineer (AI): Developing scientific AI models to tackle complex, multi-step problems across domains with an accent on sequential decision-making, reasoning, and task completion in scientific contexts. Focus on designing, training, and deploying advanced AI agents capable of performing in scientific contexts.

Location: San Francisco, CA or Cambridge, MA (Hybrid and On-Site available depending on team needs).

Salary: $148,000 - $240,000 USD

Company

hirify.global is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.

What you will do

• Design, train, and deploy advanced AI agents capable of performing sequential decision-making, reasoning, and task completion in scientific contexts.
• Develop agentic AI systems for science that perform sequential decision‑making and multi‑step reasoning to solve domain‑specific problems.
• Work on workflow/code generation from natural language intent to typed, executable steps for lab instruments.
• Create benchmarks, test suites, and telemetry to measure capability and quantify progress toward scientific goals.

Requirements

• PhD or Masters in a quantitative discipline (e.g., Computer Science, Physics, Mathematics, Engineering) with a strong background in machine learning and one domain of science (e.g. biology or materials science).
• Strong grasp of LLMs and agent architectures (planning, tool use, structured function calling, code generation) and how to adapt them to domains.
• Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experience implementing scalable solutions for complex tasks.
• Comfort collaborating across disciplines and interfacing with simulations and real lab systems.

Nice to have

• Experience building long‑horizon agents or RL for control/decision‑making; experience with model‑based or offline RL.
• Experience designing domain‑specific benchmarks and evaluation harnesses for complex scientific tasks.
• Experience with digital‑twin development, calibration, and sim‑to‑real transfer.
• Publications or open‑source contributions in AI for science (especially publications in top-tier conferences like NeurIPS, ICML, AAAI, ICLR).

Culture & Benefits

• Competitive compensation including bonus potential and generous early equity.
• Committed to equal employment opportunity.