Senior Software Engineer, Data

About this role

<p><strong>Your Impact at LILA</strong></p> <p>Join us in shaping the future of science! We are seeking <strong>Senior</strong> <strong>Software Engineers with backend experience</strong> to join our Data Platform Team (Data), 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 Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.</p> <p><strong>What You'll Be Building</strong></p> <ul> <li><strong>Design & Build APIs:</strong> Design and build high-performance, secure, and well-documented 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>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>5-8+ years of engineering experience</strong> building and deploying large-scale backend systems in production.</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> <li><strong>Experience with ORMs:</strong> Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).</li> <li><strong>Orchestration Systems:</strong> Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).</li> <li><strong>Full Stack Development</strong>: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, 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 deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.</li> </ul> <p><strong>Bonus Points For</strong></p> <ul> <li><strong>Familiarity with Python for Science</strong>: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).</li> <li><strong>Domain Background:</strong> Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.</li> <li>Experience with laboratory devices, robotics, or hardware</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>$144,000</span><span…