Lila Sciences is a startup building an AI platform that trains models on scientific literature and integrates laboratory validation to enable autonomous scientific discovery.
<p><strong>Your Impact at LILA</strong></p> <p>Join us in shaping the future of science! We are seeking a <strong>Software Engineer II with backend experience</strong> to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!</p> <p><strong>About The Team</strong></p> <p>The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.</p> <p><strong>What You'll Be Building</strong></p> <ul> <li><strong>Design & Build UI and APIs:</strong> Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.</li> <li><strong>Database Architecture & Scaling:</strong> Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.</li> <li><strong>Application Development:</strong> Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.</li> <li><strong>Performance & Reliability:</strong> Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.</li> <li><strong>Cloud & Infrastructure:</strong> Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.</li> <li><strong>Cross-Functional Collaboration:</strong> Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.</li> </ul> <p><strong>What You'll Need To Succeed</strong></p> <ul> <li><strong>Bachelor’s or Master’s degree</strong> in Computer Science, Engineering, or related field.</li> <li><strong>2-5 years of engineering experience</strong> building and deploying large-scale systems in production. You must be strong in backend.</li> <li><strong>Full Stack Development</strong>: Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)</li> <li>Hands on experience using AI coding assistants to drive productivity is required.</li> <li><strong>Communication & Collaboration</strong>: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.</li> <li><strong>Problem Solving</strong>: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.</li> </ul> <p><strong>Bonus Points For</strong></p> <ul> <li><strong>Domain Background:</strong> Exposure to laboratory software for life sciences, material sciences, or related fields.</li> <li><strong>Lab Automation Experience:</strong> Experience with laboratory devices, robotics, or hardware drivers.</li> <li><strong>Orchestration Systems:</strong> Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns</li> <li><strong>Cloud & DevOps Knowledge:</strong> Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions)</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><strong>Compensation</strong></p> <p>We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.</p> <p><strong>U.S. Benefits.</strong> 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.</p> <p><strong>International Benefits.</strong> 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.</p></div><div class="title">Expected Base Salary Range</div><div class="pay-range"><span>$120,000</span><span class="divider">—</span><span>$180,000 USD</span></div></div></div><div class="content-conclusion"><p><strong>About LILA</strong></p> <p>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.</p> <p>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.</p> <p>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.</p>