Member of Technical Staff - AI Research

Acceler8 Talent; Cambridge (MA); Hybrid; USD 170,000 - 250,000; Full time

Job summary

Acceler8 Talent seeks a Member of Technical Staff in AI Research to push the boundaries of reinforcement learning, agent systems, and multi-GPU experimentation in Cambridge, MA. The role blends original research with practical engineering to produce reproducible results.

You will collaborate with physicists and engineers on scientific reasoning and publishable work, with a hybrid work arrangement that may include some onsite presence and case-by-case remote work.

Qualifications

• 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.

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.
• Work closely with physicists and engineers on scientific reasoning and problem-solving.
• Contribute to publishable research and open-source projects.

Skills

Reinforcement Learning

LLM training

Multi-GPU training

Model evaluation

Research publications

Tools

PyTorch

TensorFlow

CUDA

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)