Job Summary:

We're looking for a hands-on software engineer to harden and extend our BEARS/CREATE lab-automation platform that supports catalyst and electrochemistry research. You'll evolve a running system by strengthening the data layer (schemas, QC, and reliability), adding modular instrument servers for HPLC, GC, and potentiostat, and refining researcher-facing web apps for run setup, live telemetry, and analysis. Working side-by-side with experimentalists and the ML team, you'll shape APIs and messaging (FastAPI, MQTT) that coordinate instruments and automate workflows, and you'll productionize the stack with containers and basic Kubernetes/CI.

Your work will directly shorten the loop from experiment to insight, improving reproducibility, traceability, and scale across multiple labs. This position can be a full-time or part time position (at least 50%).

Duties & Responsibilities:

• Work closely with the experimental team to update the lab automation frontend based on research needs
• Extend the automation lab framework with new device adapters/servers (HPLC, GC, potentiostat): drivers, parsers, validation, and metadata.
• Improve ETL reliability & schemas (PostgreSQL/mySQL); implement streaming to UIs (Streamlit/Flask) for catalyst synthesis, characterization platform
• Evolve APIs (FastAPI) and communication protocols for the lab automation platform.
• Containerize & CI (Docker; basic Kubernetes) for drivers, services, and UI.

Qualifications:

• Bachelor degree or above on relevant field e.g. Computer Science, Computer Engineering, Material Science etc.
• Strong Python programming experience for data/IO and API design; solid SQL.
• Experience with datapipe and real-time data-viz (Plotly/Streamlit).
• Experience talking to instruments (serial/TCP/USB) and IoT devices (MQTT) and parsing vendor formats.
• Good understanding of material science-related research and application of machine learning tools for scientific discovery.

Nice to have:

• Electrochemistry/chromatography data familiarity; MQTT/OPC-UA/PyVISA; Grafana; LLM/agentic workflows.