Lila Sciences, Inc.
Overview
Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by applying AI to every aspect of the scientific method and solving humankind's greatest challenges in health, climate, and sustainability. Learn more about this mission at www.lila.ai. At Lila, we are uniquely cross-functional and collaborative. We seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments where all voices are heard because experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Join us in shaping the future of science. Responsibilities
Design & Build Services and Front-ends:
Design and build high-performance, secure, and well-documented code that integrates with an ecosystem of existing services and apps. Performance & Reliability:
Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads. Cloud & Infrastructure:
Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale. Cross-Functional Collaboration:
Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows and services. What You’ll Need to Succeed
Bachelor’s or Master’s degree
in Computer Science, Engineering, or related field. 4-8 years of experience
writing software in a commercial setting. Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic) Cloud & DevOps Knowledge:
Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions). Communication & Collaboration : 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. Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability. Hands-On with Latest AI Tools : Exposure to AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or agentic frameworks, as well as experience leveraging AI to improve development performance. Experience with ORMs : Experience with and web services for CRUD services (SQLModel, FastAPI, Django). Orchestration Systems : Experience with orchestration tools (Airflow, Prefect, Temporal, Dagster). Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch). Domain Background : Exposure to laboratory software or analytics for life sciences, material sciences, or related fields. Experience with laboratory devices, robotics, or hardware drivers . Company & Equal Opportunity
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.
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Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by applying AI to every aspect of the scientific method and solving humankind's greatest challenges in health, climate, and sustainability. Learn more about this mission at www.lila.ai. At Lila, we are uniquely cross-functional and collaborative. We seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments where all voices are heard because experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Join us in shaping the future of science. Responsibilities
Design & Build Services and Front-ends:
Design and build high-performance, secure, and well-documented code that integrates with an ecosystem of existing services and apps. Performance & Reliability:
Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads. Cloud & Infrastructure:
Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale. Cross-Functional Collaboration:
Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows and services. What You’ll Need to Succeed
Bachelor’s or Master’s degree
in Computer Science, Engineering, or related field. 4-8 years of experience
writing software in a commercial setting. Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic) Cloud & DevOps Knowledge:
Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions). Communication & Collaboration : 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. Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability. Hands-On with Latest AI Tools : Exposure to AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or agentic frameworks, as well as experience leveraging AI to improve development performance. Experience with ORMs : Experience with and web services for CRUD services (SQLModel, FastAPI, Django). Orchestration Systems : Experience with orchestration tools (Airflow, Prefect, Temporal, Dagster). Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch). Domain Background : Exposure to laboratory software or analytics for life sciences, material sciences, or related fields. Experience with laboratory devices, robotics, or hardware drivers . Company & Equal Opportunity
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.
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