Matterworks is seeking a Senior Machine Learning Scientist to be a core contributor designing, building, and optimizing neural network architectures that interpret complex mass spectrometry data. You will own significant model components and drive projects from experimentation through deployment.
What You'll Do
- Design, adapt, and optimize deep learning architectures for scientific domains and data modalities within the Large Spectral Model framework.
- Own and deliver on complex ML projects, including experiment design, implementation, evaluation, and iteration.
- Write clean, well-tested code in PyTorch and NumPy to enable a high experimentation rate.
- Stay current with deep learning research and its applications in chemistry and biology; propose and prototype new ideas.
- Work closely with scientists and engineers to integrate models into product and infrastructure.
What We're Looking For
- Ph.D. or M.S. in a quantitative field (Computer Science, Chemistry, Physics, or related), or equivalent experience.
- 3+ years of hands-on experience building and deploying deep learning models.
- Strong proficiency in Python, PyTorch, and NumPy.
- Demonstrated experience designing or adapting neural network architectures.
Nice to Have
- Experience with spectral analysis, structure prediction, or molecular representation learning.
- Familiarity with scientific data formats (e.g., HDF5, mzML, Zarr).
- Publications or a portfolio of relevant projects.
Technical Stack
- Python
- PyTorch
- NumPy
Benefits & Compensation
- Competitive base salary + equity: Stock options
- Health & dental, vision, long- and short-term disability, life insurance
- 401k with company match
- Flexible work & unlimited time away policy
- Commuter benefits and parking
- Regular team meals and outings
- Company support for continued education/coursework and conference participation
Work Mode
This role is hybrid, based in Somerville, MA.
Matterworks, Inc. is an equal opportunity employer. All candidates for employment at Matterworks are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other category protected by law.





