My client are a rapidly growing AI Research Lab based in New York. After recently raising a significant seed round, they are now on a mission to scale their Machine Learning Research group. They work on foundation AI models, looking at generative AI, Diffusion modelling and LLMs. Their work intersects where core AI R&D meets Biotechnology. Specifically, they are looking at AI Drug Discovery. The founding team are very well known and the company leadership all have high-impact contributions in top journals on machine learning. Currently, they sit at 30 people, but plan to double this over the next year.
The role would be a Research Science role in machine learning. You would be working on multi-modal ML, looking at foundation models. This might be doing diffusion modelling for protein design, or modelling the language of DNA. The core part of your role will cover research, and there will be plenty of opportunities to be involved publishing in the likes of NeurIPS, ICML, Nature etc. That being said, it’s important you understand how work is shipped into a product – deploying ML models won’t be your responsibility, but it’s important you have experience working on code-bases, preferably large scale. As of now, this will be an individual contributor position – they are recruiting across the Mid, Senior and Staff levels. This doesn’t mean there aren’t management opportunities down the line as the company scale.
In terms of the people they are looking for, it’s vital you have a strong track record of core machine learning research, evidenced by publications in top journals. If you are someone who has spent time researching fundamental AI in top R&D Labs or well-known start-ups, this is also very attractive. You’ll not need to be an expert in any particular area of machine learning, but expected to have strong knowledge across Deep Learning, Diffusion Modelling and Language Modelling. Publications in these areas are great to see. The company have bases in New York and the SF Bay Area, so being based in either location is great; they have a hybrid policy.
Key Requirements:
- PhD from a top program in Computer Science, Machine Learning or closely related.
- Publications in either Deep Learning, Diffusion Modelling, Generative Modelling, Large Language Modelling, Computer Vision or closely related area of ML.
- Proficiency in Python, PyTorch/TensorFlow, Modern Software Engineering techniques and deep learning frameworks.
- Track record of research in a top AI Lab, Research Company, AI Start-Up or closely relevant organisation.
- Strong motivation to do use artificial intelligence to improve the world and make a positive mark on humanity
- Ability to present research, communicate findings, apply research to relevant products and work in multi-disciplinary teams.
If the above sounds like you, please get in touch. No Drug Discovery or Biology experience is necessary at all. If you have worked on generative protein/antibody/small molecule design, this might help your application due to its relevance, but it is by no means a requirement and we encourage people with none of that experience to apply.
The package for this role is highly competitive, with a basic cash compensation of $200,000 – $325,000 on offer. There is an equity package and bonuses available too. Above all, you’ll get the rare opportunity to work with a world-leading team, from the best Labs in the world, on live-changing machine learning technologies.
Employer-provided
Pay range in New York, United States
Exact compensation may vary based on skills, experience, and location.
Base salary
$200,000/yr – $350,000/yr