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Matterworks Tech Stack

Foundation models for mass spectrometry and biochemical omics data

Biotechnology Research Somerville, MA 51–200 employees Privately Held

Matterworks applies deep learning to mass spectrometry data for drug discovery and research. The stack—Python, PyTorch, NumPy on AWS/Azure/GCP with Apache Spark—is purpose-built for scientific computing at scale. Active projects span custom neural architectures, spectral modeling, and metabolomics integration, while hiring remains tightly focused on senior ML engineers and data specialists, reflecting early-stage focus on model development over growth.

Tech Stack 11 technologies

Core StackPython Java JavaScript AWS Apache Spark PyTorch NumPy Azure GCP HDF5 Zarr

What Matterworks Is Building

◆Challenges

Scaling environment
Messy chemical and biological datasets
Data quality and governance
Scalable data integration

▲Active Projects

Core deep learning models
Custom neural network architectures for scientific domains
Large spectral model framework
Mass spectrometry data modeling
Data management practice
Dataset intake workflow
Scalable metabolomics integration

Hiring Activity

Minimal5 roles · 0 in 30d

Department

Engineering

3

Data

2

Seniority

Senior

3

Principal

1

Staff

1

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About Matterworks

Matterworks builds Pyxis, a platform that applies foundation models to mass spectrometry and biochemical omics data. The product enables pharma and biotech teams to predict biological properties, classify disease states, and forecast R&D outcomes across drug discovery workflows. The company serves customers at scales ranging from self-service exploration to lab services and enterprise partnerships. Headquartered in Somerville, MA, the 51–200-person team is concentrated in the United States.

HeadquartersSomerville, MA

Company Size51–200 employees

Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Matterworks use?

Python, Java, JavaScript, PyTorch, NumPy, HDF5, Zarr for modeling; AWS, Azure, GCP for infrastructure; Apache Spark for distributed data processing.

What is Matterworks working on?

Core deep learning models, custom neural network architectures for scientific domains, a large spectral model framework, mass spectrometry data modeling, and scalable metabolomics integration.