Member of Technical Staff - AI Research

Acceler8; Massachusetts; Hybrid; USD 140,000 - 240,000; Full time

Job summary

Acceler8 Talent seeks a Member of Technical Staff - AI Research in Cambridge, MA, a hybrid role. You will push fundamental AI research while delivering scalable, reproducible results across engineering and science teams.

You will lead large-scale RL/agent systems experiments, work with physicists and engineers, and contribute to publishable research and open-source projects. Hybrid onsite/remote considerations apply.

Qualifications

• Strong research background with publications in AI/ML venues
• Hands-on experience in reinforcement learning, LLM training, agent systems or model evaluation
• Experience building and running multi-GPU training experiments
• Ability to independently design experiments, evaluate results and publish findings

Responsibilities

• Develop new approaches to reinforcement learning, AI agents and model reasoning
• Design and run large-scale training experiments across multiple GPUs
• Build robust evaluation frameworks, benchmarks and research tools
• Collaborate with physicists and engineers on scientific reasoning
• Contribute to publishable research and open-source projects

Skills

Research background

RL

LLM training

Agent systems

Model evaluation

Multi-GPU training

Job description

Member of Technical Staff - AI Research | Cambridge, MA (Hybrid)

I'm working with an early-stage AI research company building models and autonomous agents designed to tackle complex scientific and engineering problems.

They're looking for experienced AI Researchers who can combine original research with hands-on engineering, taking ideas from initial experimentation through to reproducible results.

The role:

• Develop new approaches to reinforcement learning, AI agents and model reasoning
• Design and run large-scale training experiments across multiple GPUs
• Build robust evaluation frameworks, benchmarks and research tools
• Work closely with physicists and engineers on scientific reasoning and problem-solving
• Contribute to publishable research and open-source projects

What they're looking for:

• Strong research background with publications at leading AI/ML conferences
• Hands-on experience in RL, LLM training, agent systems or model evaluation
• Experience building and running multi-GPU training experiments
• Ability to independently design experiments, evaluate results and deliver research outcomes

Why consider it?

An opportunity to work on fundamental AI research with direct applications to scientific discovery, alongside a team combining expertise in machine learning, physics and engineering.

Location:

Cambridge, MA | Hybrid (3 days onsite, remote considered case by case)