Senior Applied AI/ML Scientist

We are seeking an Applied AI/ML Scientist that will be responsible for developing and deploying machine learning models that solve complex, real-world scientific and industrial challenges. In this role, you will combine advanced AI/ML approaches with your domain expertise to build models that solve complex industrial problems, optimize processes, and drive real-world breakthroughs.

You will work closely with domain experts, product teams, and engineers to translate scientific problems into scalable AI solutions that drive measurable business and customer impact.

- Design, develop, and deploy machine learning and deep learning models for scientific applications (e.g., materials discovery, chemical modeling, process optimization) - Translate complex scientific and business problems into tractable AI/ML frameworks - Work with real-world structured and unstructured scientific data (e.g., experimental, simulation, and literature data) - Build and maintain data pipelines, feature engineering workflows, and model evaluation frameworks - Collaborate cross-functionally with scientists, engineers, and product managers to deliver production-ready solutions - Partner closely with Customer Success and client-facing teams to understand customer needs, translate requirements into AI/ML solutions, and support the successful deployment, adoption, and ongoing optimization of models in customer environments - Apply techniques such as supervised/unsupervised learning, generative models, and optimization algorithms - Contribute to the integration of models into scalable software platforms and APIs - Stay current with advancements in AI/ML and relevant scientific domains; evaluate and apply new methods where appropriate - Perform strategic research oriented towards improving NobleAI's core technology - Communicate findings and model outputs clearly to both technical and non-technical stakeholders - Periodic travel to customer sites and attend industry events

- Ph.D. in Chemistry, Physics, Biochemistry, Chemical Engineering, or other STEM-related fields - Degree or coursework in Machine Learning - Hands-on experience applying machine learning to real-world problems in science and engineering - Strong background in machine learning: classical and deep learning techniques (examples may include GNNs, transformers, or embedding techniques, etc.) - Strong experience in Python and associated ML frameworks (Pytorch, Tensorflow, Keras, sklearn, etc.) - Demonstrated ability to effectively communicate complex technical details at a high level - Solid understanding of statistical modeling, optimization, and algorithm design - Proven ability to deploy models into production environments

- Experience in either representation learning, geometric learning, uncertainty quantification, or unsupervised learning approaches - Experience with cloud or distributed training frameworks (Azure, AWS, GCP) and MLOps practices - Experience in scientific domains such as chemistry, materials science, or physics - Strong familiarity with molecule generation, chemical foundation models, and/or physics-informed ML - Experience with generative AI methods (e.g., diffusion models, flow matching, transformers) applied to scientific problems

- Top-tier health benefits coverage, including medical, dental, vision, disability and life insurance - Flexible paid time off & generous holidays - Remote-first with co-working access at Industrious offices - 401(k) with employer match - Equity package - Base Salary Range $190k - $220k (Depending on experience & Geographic location) - Performance-based bonus plan