Frontier RL Research Engineer - Equity & Big Compute

Recurvia; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Equity participation

Frontier AI research environment

Early-stage join with impact

Job summary

Recurvia in London is seeking an exceptional Reinforcement Learning Research Engineer to join our research team. You will design and evaluate novel RL algorithms, run large-scale experiments, and turn research into robust, production-ready systems.

You will work closely with research scientists and engineers to shape the scientific direction and build scalable infrastructure, contributing to frontier AI and holding equity participation as part of compensation.

Qualifications

• Requires MSc/PhD or equivalent in CS/ML or related field.
• Strong expertise in multi-agent reinforcement learning.
• Deep RL theory knowledge and modern ML techniques.
• Excellent Python skills and production-grade software experience.
• Strong experience with PyTorch; CUDA/JAX knowledge a plus.
• Ability to drive research and engineering projects independently.

Responsibilities

• Design, implement and evaluate novel multi-agent RL algorithms.
• Plan, execute and analyse large-scale experimental campaigns.
• Translate ideas into robust, scalable production systems.
• Collaborate with scientists to shape scientific direction.
• Improve performance, reliability and scalability of RL systems.
• Work with engineers to integrate new technologies into production.

Skills

MSc/PhD or equivalent experience

Advanced RL expertise

Python proficiency

PyTorch experience

Independent project leadership

RL theory & ML techniques

Education

MSc or PhD in CS/ML

Tools

Python

PyTorch

CUDA

JAX

Job description

Recurvia in London is seeking an exceptional Reinforcement Learning Research Engineer to join our research team. You will design and evaluate novel RL algorithms, run large-scale experiments, and turn research into robust, production-ready systems.

You will work closely with research scientists and engineers to shape the scientific direction and build scalable infrastructure, contributing to frontier AI and holding equity participation as part of compensation.