Accelerating Product Development Through Science-Based AI
Senior Applied AI/ML Scientist
Location
California
Posted
2 days ago
Salary
$190K - $220K / year
Seniority
Senior
Job Description
Senior Applied AI/ML Scientist
NobleAI
• 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
Job Requirements
- 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
Benefits
- 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
- Performance-based bonus plan
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