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Senior Applied AI/ML Scientist

3 weeks, 6 days ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS Azure Computer Vision Deep Learning Feature Engineering GCP Keras Machine Learning MLOps NLP 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 translate customer needs into AI/ML solutions and support deployment, adoption, and ongoing optimization.
  • Apply supervised and unsupervised learning methods, generative models, and optimization algorithms as appropriate.
  • Contribute to integrating models into scalable software platforms and APIs.
  • Stay current with advances in AI/ML and relevant scientific domains and evaluate new methods where appropriate.
  • Perform strategic research to improve NobleAI’s core technology and communicate findings to technical and non-technical stakeholders.

Requirements

  • Ph.D. in Geoscience, Geophysics, Production Engineering, Reservoir Engineering, or another energy-related quantitative discipline.
  • Degree or coursework in machine learning.
  • Hands-on experience applying machine learning to real-world science or engineering problems.
  • Strong background in machine learning, including classical and deep learning techniques such as CNNs, transformers, or embedding techniques, with a focus on supervised learning.
  • Strong experience in Python and ML frameworks such as PyTorch, TensorFlow, Keras, and 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.
  • Preferred experience in natural language processing, computer vision, uncertainty quantification, or unsupervised learning.
  • Preferred experience with cloud or distributed training frameworks such as Azure, AWS, or GCP and with MLOps practices.
  • Preferred experience in scientific domains such as chemistry, materials science, or energy.
  • Preferred familiarity with physics-informed ML, geological or reservoir modeling, production forecasting, or flow assurance optimization.
  • Preferred experience with generative AI methods such as diffusion models or transformers applied to scientific problems.

Benefits

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

Interested in this position?

Apply directly on the company website

Apply Now

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