Machine Learning Engineer (Generative AI)

Applied Materials
Santa Clara
Workplace: OnsiteFull timeUSD 131,000 - 180,000 annuallyFunction: Data Science & Machine LearningEducation: mastersSkills: ["Communication","Collaboration","Mentoring","Presenting complex ideas"]

Build and optimize domain-specific generative AI and large language model solutions for scientific and materials science workflows. Develop and align LLMs through pretraining, supervised fine-tuning, and post-training alignment (e.g., RLHF), with rigorous evaluation to ensure robustness and trustworthiness. Create datasets, benchmarks, and validation protocols, collaborate with scientists and engineers to identify impactful applications, and stay current by publishing original research.

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FursaFursa
Applied Materials
Applied Materials
2 months ago

Machine Learning Engineer (Generative AI)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live

Job Summary

Build and optimize domain-specific generative AI and large language model solutions for scientific and materials science workflows. Develop and align LLMs through pretraining, supervised fine-tuning, and post-training alignment (e.g., RLHF), with rigorous evaluation to ensure robustness and trustworthiness. Create datasets, benchmarks, and validation protocols, collaborate with scientists and engineers to identify impactful applications, and stay current by publishing original research.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Develop, pretrain, fine-tune, and align LLMs and generative models for scientific and materials science data, literature, and workflows.
  • •Innovate post-training methods, alignment, and evaluation for domain-specific LLMs to ensure models are robust, accurate, and trustworthy.
  • •Design and implement generative approaches to accelerate materials discovery, hypothesis generation, and hardware design.
  • •Collaborate with scientists, engineers, and cross-functional teams to identify impactful generative AI applications in materials science.
  • •Build and curate scientific datasets, benchmarks, and evaluation protocols for model validation and continuous improvement.
Travel: Low travel

Pay and Benefits

Salary: USD 131,000 - 180,000 annually
Equity and Bonus:Equity

Key Requirements

  • •MS or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or a related field.
  • •Strong background in machine learning, deep learning, NLP, and generative AI for scientific/technical domains.
  • •Hands-on experience with LLM pretraining, supervised fine-tuning (SFT), post-training alignment (e.g., RLHF), and rigorous model evaluation.
  • •Proficiency in Python and frameworks such as PyTorch or TensorFlow.
  • •Experience working with structured and unstructured scientific data (e.g., literature, experimental results, simulation outputs) to build domain-specific models.
Experience:Materials scienceScientific discoveryNLPGenerative AILarge language models
Education:Master's in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics (or related field)
Skills:CommunicationCollaborationMentoringPresenting complex ideas
Tech Stack:PythonPyTorchTensorFlowNLPLLMsRLHFLarge language models

Company Brief

Applied Materials
Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.
Industry: Industrial Machinery
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1967
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