---
title: 'Co-Op, SCADA Engineer at Lila Sciences'
canonical: 'https://feeny.ai/job/co-op-scada-engineer-lila-sciences-cambridge-hv28gbacp62z'
type: 'job'
last_seen: '2026-10-30'
---

# Co-Op, SCADA Engineer at Lila Sciences

- **Company:** Lila Sciences
- **Location:** Cambridge, MA
- **Posted:** 2026-10-30
- **Last confirmed live:** 2026-10-30
- **Apply:** https://job-boards.greenhouse.io/lilasciences/jobs/4467407009

## Job description

## Your Impact at LILA

Lila's SCADA system spans cloud and on-premise infrastructure: Ignition gateways on EC2, a historian on RDS PostgreSQL, MQTT brokers, and edge nodes at each site. Today no single view shows the health of all of it, so the team learns about failures from users rather than from monitoring.

As a co-op on the Hardware & Controls Engineering team, you will build that view: a live connectivity diagram showing how every piece connects and which links are up, backed by dashboards covering database, gateway, and edge node health. The work is read-only end to end, with read-only AWS access and SELECT-only database access, so you can explore the full system safely.

You will be based at our Alewife site in Cambridge, working alongside controls engineers and the IT/OT team. Expect wide exposure across AWS, Linux, industrial networking, Ignition, and data visualization, and a clear picture of how an industrial SCADA system fits together end to end.

## What You'll Be Building

- Build a live topology view of edge nodes, brokers, gateways, and databases with per-link status and last-seen timestamps
- Surface RDS PostgreSQL health: CPU, memory, storage growth, connection counts, replication lag, and slow queries
- Dashboard Ignition gateway and EC2 metrics, including JVM heap, tag quality, Sparkplug birth and death rates, and scan timing
- Monitor on-premise edge nodes for reachability, uptime, resource use, and last publish time
- Integrate existing sources (CloudWatch, Performance Insights, Ignition gateway metrics, broker status) into one interface
- Document the setup so the team can extend and maintain it after the term ends

## What You'll Need to Succeed

- Pursuing a bachelor's or master's degree in engineering, computer science, or a related field
- Available full time for the Spring 2027 co-op term, on-site at Alewife
- Proficiency in Python for scripting and data collection
- Comfortable working in Linux from the command line
- Working knowledge of networking fundamentals: IP addressing, subnets, ports, and routing
- Clear written communication for documenting dashboards and findings

Bonus Points For

- Exposure to AWS, particularly EC2, RDS, CloudWatch, or IAM
- Experience with Grafana, Prometheus, or similar observability tooling
- Familiarity with Ignition, MQTT or Sparkplug, or other industrial SCADA tooling
- JavaScript or React, useful for building inside Ignition Perspective

## About LILA

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.

We’re All In

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](https://www.lila.ai/candidate-privacy-policy-notice).

A Note to Agencies

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.

## About Lila Sciences

## Company Overview
- **One-liner**: Lila Sciences is building the world’s first Scientific Superintelligence platform and autonomous lab, using AI to autonomously generate hypotheses, design and run experiments, and learn from results in real time across life sciences, chemistry, materials, energy, and defense.
- **Entity Type**: Private (Privately Held) – Series A, Seed, and Grant funding rounds
- **Headquarters**: Cambridge, Massachusetts, United States
- **Founded**: Not publicly available (first funding round was Seed in March 2025)
- **Founders**: Not publicly available (founded within Flagship Pioneering’s ecosystem)

## Core Business
- **Primary industry**: AI-powered scientific discovery and autonomous laboratory platforms
- **Target customers**: B2B – research organizations, biotech, pharmaceutical, energy, materials, aerospace, and defense companies
- **Mission**: “Scientific Superintelligence to solve humankind’s greatest challenges” – accelerating discovery across medicine, materials, energy, and defense

## Products & Services
- **LILA Platform (Scientific Superintelligence)**: An AI model and operating system that autonomously executes the entire scientific method – generating hypotheses, designing experiments, running them in physical labs, and learning from results in real time.
- **AI Science Factory™ Instruments**: Proprietary hardware and robotics that serve as the “body” of the platform, enabling automated experimentation at scale.
- **Domain-specific applications**: Tailored solutions for biotech (drug discovery, protein engineering), therapeutics (mRNA, antibodies, cell therapies), energy & environment (clean fuels, catalysis, critical minerals), advanced materials, chemicals, aerospace & defense, and oil & gas.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding – USD $550.7M (as of LinkedIn data)
  - Seed Round (March 2025): $200M led by Flagship Pioneering
  - Series A (September 2025): $235M led by Braidwell and Collective Global Management
  - Series A (November 2025): $115M led by NVentures (NVIDIA)
  - Grant (January 2026): $671,400 led by ARIA
- **Notable Investors/Partners**: Flagship Pioneering, NVIDIA (NVentures), Braidwell, Collective Global Management, ARIA
- **Growth Signals**: Named #25 on the 2026 CNBC Disruptor 50 List; headcount of 308 employees (monthly growth +10.6%); 122 active job postings; operates in 6 countries (US, UK, Canada, Poland, Spain, Germany)

## Competitive Advantages
- **Proprietary AI model** that consistently outperforms other models across scientific domains in complex analysis and reasoning.
- **Autonomous physical labs** that close the loop between AI hypothesis generation and real-world experimentation.
- **“Team of Teams” operating model** enabling startup speed at scale while maintaining radical transparency and high trust.
- **General platform approach** (inspired by Rich Sutton’s “Bitter Lesson”) rather than narrow domain-specific tools, allowing broad applicability.

## Strategic Focus
- Accelerating discovery across medicine, materials, energy, and defense
- Scaling the autonomous science platform to more industries and use cases
- Building “Scientific Superintelligence” that can tackle humanity’s greatest challenges
- Continued investment in AI research, robotics, and lab automation

## Why Work Here
- **Culture**: Emphasizes velocity, trust, curiosity, truth, and grit. “Think freely, prove precisely.” A high-trust, mission-driven environment where scientists and engineers work side by side.
- **Remote/Hybrid/Office**: Roles are listed in Cambridge, MA; San Francisco, CA; and London, UK. Physical lab presence suggests significant on-site work, but some roles may offer flexibility. Policy not explicitly stated.
- **Notable perks/engineering culture**: Opportunity to work at the frontier of AI and scientific discovery; collaboration with world-renowned experts; access to cutting-edge robotics and AI infrastructure; strong emphasis on learning and teaching (“generous teachers and eager learners”).

## Sources
1. [lila.ai](https://www.lila.ai/)
2. [lila.ai/about](https://www.lila.ai/about)
3. [lila.ai/open-roles](https://www.lila.ai/open-roles)
4. [LinkedIn - Lila Sciences](https://www.linkedin.com/company/lila-sciences)
5. [Greenhouse Job Board](https://job-boards.greenhouse.io/lilasciences/jobs/4246302009)

## Other roles at Lila Sciences

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- [Co-Op, Bayesian Methods for Complex Decision Making](https://feeny.ai/job/co-op-bayesian-methods-for-complex-decision-making-lila-sciences-cambridge-ndt2w02kgvj2) — Cambridge, MA / San Francisco, CA
- [Co-Op, Structuring Scientific Data for Discovery](https://feeny.ai/job/co-op-structuring-scientific-data-for-discovery-lila-sciences-cambridge-57tgh64e8y0k) — Cambridge, MA / San Francisco, CA
- [Co-Op, Electron Microscopy](https://feeny.ai/job/co-op-electron-microscopy-lila-sciences-cambridge-nj1aaxqp55xm) — Cambridge, MA
- [Co-Op, Finance](https://feeny.ai/job/co-op-finance-lila-sciences-cambridge-8p0szx7ty94c) — Cambridge, MA
- [Associate Director/Director, Frontier and AI Product Counsel](https://feeny.ai/job/associate-director-director-frontier-and-ai-product-counsel-lila-sciences-7z94cshd3d66) — Cambridge, MA / San Francisco, CA
- [Co-Op, Robot Perception & State Estimation](https://feeny.ai/job/co-op-robot-perception-state-estimation-lila-sciences-cambridge-yznrym7yenxa) — Cambridge, MA
- [Co-Op, AI Nucleic Acid Design](https://feeny.ai/job/co-op-ai-nucleic-acid-design-lila-sciences-san-francisco-jna9hpj3dsxn) — San Francisco, CA
- [Co-Op, Reaction Prediction & Benchmarking](https://feeny.ai/job/co-op-reaction-prediction-benchmarking-lila-sciences-cambridge-yc1ec2e9sfb4) — Cambridge, MA / San Francisco, CA
- [Co-Op, Agentic Simulations for Materials Science](https://feeny.ai/job/co-op-agentic-simulations-for-materials-science-lila-sciences-cambridge-z1m0175gttp2) — Cambridge, MA / San Francisco, CA