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Staff Software Engineer - AI Lab Execution System

Lila SciencesCambridge, MA USA; San Francisco, CA USA
On-site Full-time $192K/yr - $238K/yr

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Experience Level

Mid to Senior

Qualifications

To Excel in This Role, You Will Need: A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 4-6 years of experience in engineering, focusing on building and deploying large-scale systems in production. Strong expertise in either front-end, back-end, or data modeling and design is essential. Proficiency in Typescript, React, and Python: A strong background in React and Typescript is required.

About the job

Your Contribution at Lila Sciences

Lila Sciences is on the lookout for a dynamic Staff Software Engineer to join our innovative AI Lab Execution System team. In this pivotal role, you will have the opportunity to design, develop, and enhance intelligent, data-driven applications, with a strong emphasis on front-end development. Your focus will include the creation of user interfaces, services, high-performance APIs, and databases, ensuring seamless integration of advanced AI frameworks into our scientific analytics and laboratory workflows.

Collaborating closely with ML researchers, platform engineers, and scientists, you will develop systems capable of managing diverse workloads and scaling efficiently. This includes working with structured SQL databases, data lake houses, and vector databases. If you are passionate about creating high-performance, elegant systems that make a real scientific impact, we invite you to apply!

Your Responsibilities Include:

  • UI and API Design & Development: Create high-performance, secure, and well-documented user interfaces and APIs that integrate seamlessly with AI-driven applications.
  • Database Design & Management: Develop schemas and manage various data systems (SQL, NoSQL, Vector DBs) to ensure optimal performance and scalability.
  • Application Development: Lead the development of both front-end and backend services, prioritizing performance, maintainability, and reliability.
  • Performance Optimization: Identify and resolve system bottlenecks, ensuring high availability and low-latency performance across extensive workloads.
  • Cloud Infrastructure: Utilize AWS services, Kubernetes, and modern DevOps practices to build and deploy scalable production systems.
  • Collaborative Development: Work alongside ML researchers and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

About Lila Sciences

Lila Sciences is dedicated to pioneering the next generation of AI-driven scientific platforms that transform the landscape of scientific research. By leveraging cutting-edge technology and innovative approaches, we strive to enhance the efficiency and efficacy of laboratory workflows.

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