AI Research Scientist/ Research Engineer: Materials Discovery

Logical Intelligence • San Francisco, CA

3d

About The Position

Logical Intelligence is hiring for its materials discovery team to develop AI systems that propose and evaluate candidate molecules, with the goal of accelerating discovery of materials for technologies including light emitters, semiconductors, batteries, electric vehicles, and chips. The role involves building a discovery loop that incorporates chemistry and physics, using energy-based models and other approaches to search chemical space efficiently. The scientist or engineer will work closely with partner laboratories so that synthesis and measurement results inform model development, as part of an interdisciplinary team of chemists, physicists, machine learning scientists, and engineers.

Requirements

• Background in machine learning, computational chemistry, physics, or a related field, with a PhD or a Master’s degree plus relevant industry experience.
• Hands-on experience building machine learning models for real scientific problems.
• Knowledge of chemistry or a genuine interest in learning it alongside chemists.
• Experience designing evaluations and experiments that correlate with downstream performance.
• Strong record of impactful research, demonstrated through publications, patents, open-source software, or methods used in real discovery programs.
• Excellent scientific writing and communication skills, and comfort working in an interdisciplinary team.

Nice To Haves

• Familiarity with energy-based models, diffusion or score-based models, or similar generative approaches, and interest in developing deeper expertise.
• Hands-on research experience with energy-based models or methods combining learning with search and optimization.
• Experience with molecular machine learning, such as property prediction, generative molecular design, machine-learning interatomic potentials, or quantum-chemistry workflows such as DFT.
• Experience with closed-loop design using real laboratory feedback.

Responsibilities

• Build and improve AI systems for the materials discovery loop, including candidate generation, screening, and selecting molecules for testing.
• Develop energy-based models that combine learned representations with physical and chemical knowledge to search chemical space more efficiently.
• Own model evaluation, including held-out chemical-family benchmarks, comparison with quantum-chemistry calculations and experiments, uncertainty calibration, prospective testing, and tracking model versions.
• Compare AI predictions with measurements, investigate disagreements, and translate findings into model changes in collaboration with AI researchers and engineers.
• Design experiments with partner laboratories to make each round of synthesis and testing as informative as possible.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree