About Altrove

Founded by a successful repeat entrepreneur and a top technical CTO (PhD Materials Science from Cambridge University), we're a rapidly growing startup, supported by Tier 1 investors and partners. We're tackling the biggest materials challenges of the century, creating better alternatives to the most critical materials. At altrove, we are bridging the gap between crystal structure prediction and inorganic material synthesis by using our deep AI expertise and high-throughput laboratory.

Job Description

We are looking for a Research Scientist/Engineer with strong machine learning fundamentals to fine-tune, deploy, and operationalize in order to power Altrove's internal AI scientist. You'll be building models and pipelines to help understand the modelling and reasoning of scientific research in Altrove's high-throughput lab. You will be deploying tasks at the intersection of ML research, software engineering, and materials science.

What you'll do:

• Build and maintain ML training and inference pipelines that directly interface with scientific experiments
• Develop algorithms that operate well in high-noise environments while reasoning on obtained results
• Deploy pipelines across distributed HPC/Cloud systems
• Collaborate with computational and experimental materials scientists
• Contribute to data management

Qualifications

• A degree in Computer Science, Applied Mathematics or a related technical field, as well as subsequent work experience (of PhD) applying ML methods
• Strong machine learning fundamentals
• Solid PyTorch experience and ability to build reliable training pipelines
• Experience fine-tuning pretrained models
• Deep learning experience on multimodal or scientific data
• Good judgment in low-data, noisy-data settings
• Rigorous evaluation habits and strong experimental discipline

Nice to have

• Experience with Markov Processes, active learning, and/or Bayesian optimisation
• Experience with materials foundation models
• Familiarity with LLM-based scientific workflows
• Experience with modern ML development (training, evaluation, inference, distributed systems).

You will work on solving a generational problem along with a world-class team. You will have the possibility to own shares in the company and will work in a fast-paced, fascinating environment.