Research Engineer

Research Engineer – Foundational Models

We’re partnering exclusively with a newly launched, well-capitalised startup that has just secured $50M in seed funding to tackle some of the hardest problems in AI. With a world-class founding team and ambitious vision, they’re now hiring exceptional Research Engineers to help build and train next-generation foundational models from the ground up.

The Role

As a Research Engineer, you will sit at the intersection of research and engineering, contributing directly to the development of large-scale foundational models. You’ll work closely with leading researchers and engineers to turn novel ideas into production-ready systems.

You will:

* Design, implement, and train large-scale machine learning models

* Work on distributed training systems and optimization at scale

* Contribute to research that pushes the boundaries of generative AI and foundational models

* Collaborate closely with a small, high-calibre team to rapidly prototype and iterate

* Help define best practices across experimentation, evaluation, and deployment

What We’re Looking For

* Strong background in machine learning, deep learning, or related fields

* Proven experience training large models or working with complex ML systems

* Proficiency in Python and modern ML frameworks (e.g. PyTorch, JAX, TensorFlow)

* Solid understanding of distributed systems or high-performance computing

* Ability to move between research thinking and practical implementation

* Curiosity, ownership, and a desire to solve difficult technical problems

Nice to Have

* Experience with LLMs, multimodal models, or reinforcement learning

* Publications at top-tier conferences (e.g. NeurIPS, ICML, ICLR)

* Background in scaling infrastructure for ML workloads

* Experience working in fast-paced startup environments

Why Join?

* $50M seed funding – strong runway and backing to build something ambitious

* Work alongside top-tier talent in AI research and engineering

* Opportunity to contribute to foundational technology from the earliest stage

* High ownership, autonomy, and impact

* Competitive compensation + meaningful equity

Location

* Open to candidates across key tech hubs (US-based preferred)