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Edison Scientific

AI platform for scientific R&D workflows

Member of Technical Staff, Machine Learning Engineer

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 5 years of a strong track record in applied machine learning research and applying machine learning methods to real-world problems.
  • Experience across the machine learning lifecycle, including data pipelines and provenance, model training, model deployment, and validation in production systems.
  • Fluency in PyTorch, JAX, or an equivalent framework.
  • Demonstrated experience conducting experimentation in academic or industry settings.
  • Strong programming expertise and the ability to adapt to technical challenges across the data, machine learning, and large language model software stack.

Responsibilities

  • Interpret qualitative challenges in building artificial intelligence agents for science as well-formulated, optimizable problems.
  • Build environments in which to train and deploy artificial intelligence agents that solve scientific tasks.
  • Work with scientists to formulate and scale training data pipelines, ensuring observability and reproducibility.
  • Lead training of large-scale large language model-based systems, including building internal infrastructure to improve the efficiency of experimentation and production training runs.
  • Build efficient and flexible inference infrastructure that supports complex sampling algorithms and custom architectures.
  • Develop and extend the experimentation platform for internal tools and projects.
  • Collaborate with a multidisciplinary team of artificial intelligence researchers, chemists, and biologists.

Desired Qualifications

  • PhD in Machine Learning, Computer Science, or another quantitative field.
  • Familiarity with leveraging and managing distributed computing resources.
  • Background architecting complex distributed systems.

About the Company

Edison Scientific

AI platform for scientific R&D workflows

Edison Scientific provides an AI-powered platform that unifies research tasks in one environment. It combines literature synthesis, data analysis, molecular design, and the creation of publication-ready figures and reports so researchers can move from hypothesis to validated results without switching between many tools. The platform uses natural language processing and machine learning to digest scientific literature and data, automate workflows, and run tasks in parallel to speed up discovery. Compared with competitors, Edison Scientific stands out by offering an integrated, end-to-end R&D workflow that links literature, data, and design in a single platform, reducing manual handoffs and enabling scalable research. The company’s goal is to streamline R&D processes, shorten the time to insight, and help organizations rapidly validate findings and publish their work.

Company size
51-200
Company stage
Seed
Total funding
$70M
Headquarters
San Francisco, CA
Founded
2025

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