Software Engineer - Lab Automation (Data Pipelines + Frontend) at BERKELEY EDUCATION ALLIANCE FOR RESEARCH IN SINGAPORE LIMITED
Singapore, , Singapore -
Full Time


Start Date

Immediate

Expiry Date

04 Dec, 25

Salary

7500.0

Posted On

05 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computer Engineering, Mqtt, Computer Science

Industry

Information Technology/IT

Description

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%).

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.

How To Apply:

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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.
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