Quick Summary
Your Impact at LILA Lila Sciences is building the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.
Lila Sciences is building the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of discovery by applying AI to every aspect of the scientific method, helping scientists solve challenges in human health, climate, and sustainability at a new pace and scale.
As a Co-Op, Automation Systems Engineer / Automation Software Developer, you will work closely with the Automation, Software, and Robotics teams on Lila’s monitoring and anomaly detection capabilities. You will help connect SCADA telemetry and camera data pipelines, train detection models that flag deviations from expected operating envelopes, and build alerting capabilities that help operators address issues accurately and effectively.
The result is an operator-facing monitoring experience that works with automated lab equipment to catch and surface problems as they happen.
- Build data pipelines that support real-time anomaly detection.
- Train detection models to identify deviations from expected operating envelopes.
- Develop alerting workflows that help operators diagnose issues quickly.
- Collaborate with Automation, Software, and Robotics teams on system integration.
- Contribute to an operator-facing UI for lab monitoring and issue surfacing.
- Pursuing or completed a Bachelor’s or Master’s degree in Computer Science, Automation, Engineering, or a related quantitative discipline, with foundational coursework in machine learning and at least one scientific domain such as biology, chemistry, or materials science.
- Proficiency in Python.
- Experience working with data pipelines, streaming systems, or version-controlled software projects.
- Interest in building systems that interact with real lab equipment and messy real-world signals.
Nice to Have
~1 min read- Experience in wet labs or laboratory automation environments.
- Familiarity with SCADA systems, liquid handlers, analytical equipment, or lab instrumentation.
- Experience with time-series data or signal processing.
- Exposure to deployed ML systems or model performance in real-world conditions.
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Location & Eligibility
Listing Details
- Posted
- June 25, 2026
- First seen
- June 25, 2026
- Last seen
- June 25, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- June 25, 2026
Signal breakdown
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