Mirror Physics

AI Researcher: Multimodal Understanding

New York City

H1B sponsorship availableDetected 407 days ago

PythonKubernetesMachine LearningPyTorchLLMsRAGResearchCommunicationCollaboration

About the role

Designing materials and chemicals to address society's most pressing challenges will require joint reasoning across the domains of language, vision, and chemical structure.

Develop training pipelines for large-scale pre-training and instruction tuning on multi-GPU/TPU clusters
Create novel evaluations for cross-modal reasoning (text→structure, image→reaction pathway, etc.) and physical consistency.
Collaborate with AI, applied science, and engineering teams to build a product pipeline by integrating multimodal embeddings into search, reasoning agents, and generative design loops.

Proven track record shipping large-scale generative or contrastive models (e.g., LLMs, diffusion, VAE, CLIP, NeRF, equivariant GNNs).
Strong publication or open-source track record in ML for physical sciences.
Familiarity with quantum chemistry, atomistic simulation, or chemistry/materials science

Fluency in Python plus modern ML stacks (PyTorch/JAX) and familiarity with distributed training tooling (CUDA, NCCL, Slurm/K8s/Ray).
Preferred Extras

Competitive salary + meaningful equity
Full health, dental, and vision benefits for you and your family
Personal fitness budget
Unlimited PTO and all national holidays
Design & build multimodal architectures fusing text, vision, and chemical structure.
Ph.D. or M.S./B.S. with equivalent research record in Computer Science, Materials Science, Chemistry, or related field with emphasis on machine learning
3+ years research experience with at least two modalities (language, vision, 3-D molecules/point clouds, graphs).

Mirror is an equal-opportunity employer.
We celebrate diversity and are committed to creating an inclusive environment for all employees.

This listing is sourced directly from Mirror Physics's careers page and normalized into a canonical job model.