Research Engineer, Materials Science
$141k - $202k • Remote • Mountain View, California, US
Posted 29d ago
Job Location
Mountain View, California, US
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Google DeepMind is seeking a Research Engineer to join their materials science team. This role involves accelerating the discovery of new functional materials by integrating artificial intelligence, computational simulation, and automated experimentation. You will collaborate with a diverse interdisciplinary team of domain experts, ML researchers, and engineers. The work focuses on pioneering research in various scientific domains, enabling the validation of early ideas and building infrastructure for promising research lines. You will contribute your scientific domain knowledge to the team's collective expertise.
Responsibilities
- Plan and perform rapid prototyping of machine learning techniques applied to scientific problems.
- Undertake exploratory analysis to inform experimentation and research directions.
- Improve model architectures and training procedures of machine learning models.
- Implement tools, libraries, and frameworks to accelerate research.
- Report and present software developments, experimental results, and data analysis clearly.
- Collaborate with internal and external scientific domain experts.
Requirements
- Degree in computer science, electrical engineering, science, mathematics, or equivalent experience.
- Experience applying software engineering principles in a scientific research environment.
- Knowledge of linear algebra, calculus, and statistics equivalent to at least first-year university coursework.
- Experience exploring, analyzing, and visualizing large and noisy datasets.
- Experience using Jax, PyTorch, TensorFlow, NumPy, Pandas, or similar ML/scientific libraries.
- Specific domain expertise in areas like inorganic chemistry, solid-state physics, or materials synthesis (preferred).
- Experience applying modern deep learning architectures (e.g., transformers, diffusion models) to chemistry or material science challenges (e.g., ML force fields) (preferred).
- Experience running large-scale scientific simulations (e.g., molecular dynamics, computational chemistry simulations) on Cloud or HPC clusters (preferred).
- Experience developing custom LLM agents or tool-using systems (preferred).
- Experience with concurrent and distributed software algorithms and architectures (preferred).
- Masters or PhD in computer science, electrical engineering, science, mathematics, or equivalent experience (preferred).
Benefits
- Bonus
- Equity
- Benefits