Assistant Software Engineer - Autonomous Discovery Platforms; MADSCi

Overview

Argonne National Laboratory’s Rapid Prototyping Lab (RPL), part of the Data Science and Learning division, seeks a Software Engineer to serve as a technical lead for the Modular Autonomous Discovery for Science (MADSci) framework, a Python‑based platform that orchestrates self‑driving laboratories across materials science, chemistry, and the biosciences. MADSci is the software backbone of Argonne’s Autonomous Discovery initiative, integrating instruments, robots, AI/ML decision agents, and data pipelines into reproducible, closed‑loop scientific experiments at scales and speeds that exceed traditional human‑led methods.

• Lead day‑to‑day development of the MADSci framework: design and implement new features, triage and resolve bugs, review pull requests, and shepherd releases through the project’s CI/CD pipeline.
• Own the architecture of a Python microservices system spanning workflow orchestration, resource and inventory tracking, distributed event logging, experiment management, and device integration.
• Collaborate with experimental scientists and robotics engineers to onboard new instruments, design experiment workflows, and translate scientific goals into robust software abstractions.
• Maintain and grow the contributor community, including external collaborators at other DOE laboratories, universities, and industrial partners.
• Triage issues, review external contributions, and represent the project at workshops, conferences, and working groups.
• Operate and improve production deployments of MADSci in active autonomous laboratories at Argonne, including monitoring, observability (Open Telemetry), backups, migrations, and on‑call support during experimental campaigns.
• Mentor early‑career staff, students, and interns contributing to MADSci and to autonomous‑laboratory projects more broadly.
• Contribute to proposals, publications, and outreach describing MADSci and its scientific impact (e.g., journal articles, conference talks, the JOSS publication, documentation).

• RD2:
  Bachelor’s degree and 5+ years of experience or Master’s and 3+ years in computer science, or a PhD and 0+ years in software engineering, or a related computational discipline.
• Demonstrated proficiency in modern Python (3.10+), including type‑annotated code, packaging, and testing.
• Practical experience designing and maintaining production‑quality software: version control (Git/Git Hub), code review, automated testing, CI/CD, semantic versioning, and structured release management.
• Familiarity with at least one web service framework (e.g., FastAPI, Flask, Django) and with HTTP/REST API design.
• Working knowledge of relational and/or document databases (e.g., PostgreSQL, MongoDB‑compatible stores) and of containerized deployment (Docker, docker compose).
• Strong written and verbal communication skills, including the ability to write clear technical documentation for both developer and end‑user audiences.
• Demonstrated ability to work effectively as part of a small, cross‑disciplinary team and to collaborate with non‑software domain experts (scientists, instrument operators, hardware engineers).
• Ability to model Argonne’s core values of impact, safety, respect, integrity and teamwork.

• Software engineering depth: experience designing microservice or service‑oriented systems, including service discovery, schema management, and inter‑service communication patterns.
• Hands‑on experience with Pydantic v2, SQLModel/SQL Alchemy, or comparable typed‑data and ORM frameworks.
• Experience maintaining a multi‑package monorepo (e.g., PDM, uv, Poetry work spaces) with shared types and coordinated releases.
• Experience with observability tooling:
  Open Telemetry, distributed tracing, structured logging, metrics dashboards.
• Experience as a maintainer of an open‑source project, including triaging external issues, reviewing community contributions, and managing a public roadmap.
• Familiarity with frontend development (Vue 3, Type Script) sufficient to coordinate with frontend collaborators on dashboard and TUI features.
• Robotics, lab automation, and self‑driving labs: experience integrating scientific…