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Senior Applied AI/ML Scientist

2 months, 3 weeks ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS Azure Deep Learning Feature Engineering GCP Generative AI Keras Machine Learning MLOps Python PyTorch Scikit-learn TensorFlow Transformers
Apply Now
NobleAI

NobleAI

NobleAI is a California-based software company specializing in AI technologies for research and development. Their AI software enables enterprises to accelerate R&D processes, develop sustainable chemical and material products, and achieve significant ...

Life Sciences Tools & Services
11-50
Founded 2018
View All Jobs 4

Description

  • Design, develop, and deploy machine learning and deep learning models for scientific applications such as materials discovery, chemical modeling, and process optimization.
  • Translate complex scientific and business problems into tractable AI/ML frameworks.
  • Work with structured and unstructured scientific data, including 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 with Customer Success and client-facing teams to understand customer needs and support model deployment, adoption, and ongoing optimization.
  • Apply supervised learning, unsupervised learning, generative models, and optimization algorithms to real-world problems.
  • Contribute to integrating models into scalable software platforms and APIs.
  • Stay current with advances in AI/ML and relevant scientific domains and apply new methods where appropriate.
  • Perform strategic research to improve NobleAI’s core technology.
  • Communicate findings and model outputs clearly to technical and non-technical stakeholders.
  • Travel periodically to customer sites and industry events.

Requirements

  • Ph.D. in Chemistry, Physics, Biochemistry, Chemical Engineering, or another STEM-related field.
  • Degree or coursework in machine learning.
  • Hands-on experience applying machine learning to real-world science and engineering problems.
  • Strong background in machine learning, including classical and deep learning techniques such as GNNs, transformers, or embedding techniques.
  • Strong Python experience with ML frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn.
  • Demonstrated ability to communicate complex technical details effectively at a high level.
  • Solid understanding of statistical modeling, optimization, and algorithm design.
  • Proven ability to deploy models into production environments.
  • Experience in representation learning, geometric learning, uncertainty quantification, or unsupervised learning is preferred.
  • Experience with cloud or distributed training frameworks such as Azure, AWS, or GCP and MLOps practices is preferred.
  • Experience in scientific domains such as chemistry, materials science, or physics is preferred.
  • Familiarity with molecule generation, chemical foundation models, or physics-informed ML is preferred.
  • Experience with generative AI methods such as diffusion models, flow matching, or transformers applied to scientific problems is preferred.

Benefits

  • Base salary range of $190k-$220k depending on experience and geographic location.
  • Top-tier health benefits covering medical, dental, vision, disability, and life insurance.
  • Flexible paid time off with generous holidays.
  • Remote-first work arrangement with co-working access at Industrious offices.
  • 401(k) with employer match.
  • Equity package.
  • Performance-based bonus plan.

Interested in this position?

Apply directly on the company website

Apply Now

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