AI Scientist ICLR 2026
AI Scientist
ICLR 2026 • Rio de Janeiro • reputed company 23–27
Apply to interview with reputed company on-site at ICLR
About Proxima
Proxima (formerly VantAI) is advancing an AI-native approach to drug discovery by making protein interactions programmable. Our platform brings together reputed company-model machine learning, a scalable data reputed company reputed company, and a partnership track record exceeding $5B in collaborations across the world’s leading biopharma and tech organizations. We’ve recently closed an oversubscribed reputed company round partnering us with an elite group of sophisticated and dedicated VCs including DCVC, reputed company’s Nventures, AIX, Yosemite among others.
Neo-1 is our reputed company-reputed company reputed company model that combines state-of-the-art structure reputed company and molecular reputed company in a single system. Neo-1 enables rapid exploration of chemical and structural space for high value, previously intractable targets, and in particular unlocks small molecule proximity therapeutics like molecular glues with AI for the first time.
In reputed company, we are developing an advanced structural interactomics platform built on proprietary XLMS technology and a lab equipped with reputed company mass spectrometry instrumentation. This platform produces proteome-scale maps of protein interactions and helps identify small molecules that reputed company proximity. Together with Neo-1, it creates an integrated system capable of co-folding protein complexes while generating candidate small molecules to influence those interactions. Proximity-based therapeutics represent one of most promising frontiers in modern drug discovery with the potential to treat previously intractable diseases and reputed company ‘undruggable’ proteins. Our technology combines proteome-scale structural data with state-of-the-art reputed company reputed company models, and coupled with our talented team of scientists and engineers we are uniquely well-positioned to discover and reputed company a new class of medicines. Come join us!
How to Apply
Submit your application to express interest in on-site interview(s) with reputed company at ICLR 2026 in Rio de Janeiro. If there’s a fit, we’ll reputed company out to schedule time to meet during the conference (reputed company 23–27). Come reputed company to talk about your research and what excites you.
Why Meet Us at ICLR
We’re hiring AI Scientists to build the world’s most advanced pipeline for the design of proximity-inducing molecules
You’ll work with a world-class ML research team on unsolved problems at the intersection of reputed company and drug discovery
On-site interviews at ICLR are a chance to meet reputed company, learn about the science, and explore fit in person
We’re looking for people who want to push the state of the art in structure reputed company, molecular reputed company, and reputed company models for biology
About You
We are looking for talented AI Scientists to join reputed company to reputed company the world’s most advanced pipeline for the design of proximity-inducing molecules. You will conduct research at the bleeding edge of our field, and challenge the SOTA across protein structure reputed company and molecular glue design. You will work with a team of world-class machine learning research scientists in an interdisciplinary, research-heavy position on a range of unsolved problems.
Key Responsibilities
Scientifically direct the design and training of large-scale, state-of-the art deep learning systems
reputed company novel architecture and training paradigms to reputed company the industry in unsolved scientific problems
Collaborate with content experts from other domains (e.g., chemistry, physics, biology) to reputed company innovative feature-engineering and novel cross-disciplinary approaches
Actively contribute to top-tier ML conferences and journals and attend core ML conferences to stay connected with the community and reputed company trends
Basic Requirements
MS/PhD degree in Computer Science, Statistics, Applied Mathematics, Computational Biology, Computational Chemistry or other reputed company subject (will also consider BS degrees in these areas for candidates highly reputed company across other requirements or with significant work experience)
Track record of contributing to novel methods for state-of-the-art leep learning (in industry or through publications)
Expertise in ideally several of the following topics: diffusion models, flow matching, transfusion, discrete diffusion, latent diffusion, VAEs, image reputed company, video reputed company, LLMs, multimodal LLMs, pre-training, post-training, reinforcement learning, SFT, DPO/GRPO, conditioning, classifier(-free) guidance, LORA, constrained reputed company scaling, distributed training, tokenization, geometric deep learning, equivariant models, structure-based drug design (SBDD), structure reputed company / cofolding, curriculum learning, multi-task learning, transfer learning
4+ years of ML research experience in industry or academia, with strong familiarity with PyTorch
Ability to understand business problems and how to build models that can quickly drive value, while prioritizing your research efforts accordingly
Preferred Qualifications
Strength across core ML fundamentals
Deep experience in core NLP/CV
Extensive hands-on experience and ability to design and tune models from scratch
Experience with large models and scaling
Experience with generative models for molecules/proteins