--- title: 'Automation Engineer I/II, Sustaining Engineering & Lab Operations at Lila Sciences' canonical: 'https://feeny.ai/job/automation-engineer-i-ii-sustaining-engineering-lab-operations-lila-sciences-2wp1t59bbm9s' type: 'job' last_seen: '2026-11-06' --- # Automation Engineer I/II, Sustaining Engineering & Lab Operations at Lila Sciences - **Company:** Lila Sciences - **Location:** Cambridge, MA - **Compensation:** $76k–$125k - **Posted:** 2026-11-02 - **Last confirmed live:** 2026-11-06 - **Apply:** https://job-boards.greenhouse.io/lilasciences/jobs/4414378009 ## Job description ## Your Impact at LILA Lila Sciences is hiring Automation Engineers for the AI Science Factory (AISF), the automated platform behind our work in drug discovery, bioengineering, and advanced materials. You will join Sustaining Engineering & Lab Operations (SELO), the group responsible for keeping the platform running and improving it. You own both halves of that: operating and recovering the workcells through your shift, and developing the changes that make them more reliable and higher throughput. SELO is a multidisciplinary group of automation, mechanical, and controls engineers, staffed across shifts. Most problems worth your time cross those lines — a scheduling error that turns out to be a sensor, a throughput ceiling that turns out to be a gripper tolerance. You will bring the operational evidence and work the problem with them to a real fix. The platform runs production across shifts, so improvement work is not something you fit into idle time. You plan it, negotiate the downtime with Research Operations, schedule it into an approved window, and verify the change held before returning the system to service. Doing that well takes as much coordination as engineering. Handoff is part of the job rather than an afterthought. You give and receive a structured handoff at shift overlap, and document events, decisions, and open issues clearly enough that the other shift can act on them without coming back to you. This is a full-time, on-site role in Cambridge, MA. Shifts This role is shift-based, and we are hiring for both shifts: - First shift — 7:00 AM–3:00 PM, weekdays - Second shift — 2:00–10:00 PM, weekdays The shifts overlap for one hour so the outgoing and incoming engineers can hand off directly. Shift assignments are permanent rather than rotating — you will not be moved between shifts. Both shifts carry the same responsibilities, the same level expectations, and the same development ownership. Let us know your preference when you apply. ## What You'll Be Building - Own operation of the AISF workcells during your shift — triage instrument faults, software errors, and run failures as they surface, recover stalled runs, and decide what gets resolved in shift versus stabilized and carried across the handoff. - Drive continuous improvement of the systems and workflows you operate: identify where reliability, throughput, or recoverability falls short, propose the change, and see it through implementation and verification. - Plan improvement and maintenance work around live production — coordinate required downtime with Research Operations, schedule into approved windows, and confirm the change held before returning the system to service. - Work with SELO mechanical and controls engineers to resolve problems spanning hardware, controls, integration, and software, bringing the operational evidence needed to find root cause. - Execute preventive maintenance and calibrations on schedule, and coordinate vendor service, parts, and spares for issues in your scope. - Coordinate with on-shift Research Operations scientists to prioritize recovery when multiple issues compete, and keep active experiments moving with their scientific constraints in view. - Extend the runbooks, recovery playbooks, and diagnostic tooling the team works from, so the next engineer to hit a recurring problem resolves it faster. - Document shift events, decisions, and open issues, and run structured handoff in both directions at shift overlap. - Surface recurring failure patterns and process gaps to SELO so root causes and process weaknesses get addressed rather than absorbed. ## What You'll Need to Succeed - Bachelor's degree in Engineering, Biology, Chemistry, Materials Science, Computer Science, or a related field, or equivalent hands-on experience. - 1+ years of hands-on experience with lab automation, lab instrumentation, or production operations in a life sciences or physical sciences environment. - Ability to troubleshoot electro-mechanical equipment and software systems independently and decide when to escalate. - Strong written communication — you will be documenting problems for engineers on other shifts and handing off to a team that depends on the clarity of what you wrote. - Ability to work effectively across disciplines with mechanical, controls, and software engineers, and with scientific teams. - Comfort working in a live production environment where scientists depend on the systems you are working on. - Availability to work either the first or second shift schedule listed above, on site in Cambridge, MA. Bonus Points For - Experience with liquid handlers, plate-based workflows, automated storage, or high-throughput screening instrumentation. - Familiarity with lab scheduling or workflow orchestration software (Cellario, Overlord, Green Button Go, or similar). - Scripting or light programming ability (Python, C#, or similar) for log analysis, diagnostics, or tooling. - Familiarity with scientific processes and the constraints that come with them — sample stability, timing windows, reagent handling, and why a deviation matters to the result and not just to the run. - Exposure to robotic integration platforms or multi-instrument workcell environments. - Experience executing preventive maintenance programs or coordinating vendor service relationships. - Background in a multi-shift or continuous operations environment where structured handoffs were part of the workflow. - Experience with continuous improvement practices — measuring a system, changing it, and confirming the change held. ## Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $75,600—$124,800 USD ## 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 - [Director / Senior Director, Intellectual Property, Life Sciences](https://feeny.ai/job/director-senior-director-intellectual-property-life-sciences-lila-sciences-663mx8sk9dpg) — Cambridge, MA / San Francisco, CA - [Co-op, Agentic and Generative Protein Design](https://feeny.ai/job/co-op-agentic-and-generative-protein-design-lila-sciences-cambridge-avtbwmeq8bq9) — Cambridge, MA / San Francisco, CA - [Co-Op, Targeted Non-Viral Delivery](https://feeny.ai/job/co-op-targeted-non-viral-delivery-lila-sciences-cambridge-g7gc30z235rg) — Cambridge, MA - [Co-Op, AI-Driven Equation Discovery](https://feeny.ai/job/co-op-ai-driven-equation-discovery-lila-sciences-cambridge-hdvks2gddm7a) — Cambridge, MA / San Francisco, CA - [Co-Op, Editorial Content](https://feeny.ai/job/co-op-editorial-content-lila-sciences-cambridge-wxs4v4cxc0av) — Cambridge, MA - [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, SCADA Engineer](https://feeny.ai/job/co-op-scada-engineer-lila-sciences-cambridge-hv28gbacp62z) — Cambridge, MA - [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