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Principal Full Stack Software Engineer

Lila SciencesSan Francisco, CA USA
On-site Full-time $204K/yr - $272K/yr

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Experience Level

Mid to Senior

Qualifications

Qualifications for Success Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Experience: 8-15 years of engineering experience in building and deploying large-scale systems in a production environment. Strong expertise in either front-end or backend development is essential. Technical Skills: Proficiency in Typescript, React, and Python is required.

About the job

Your Contribution at Lila Sciences

We are on the lookout for a Principal Software Engineer with full stack proficiency to become an integral part of our software team. You will play a key role in shaping the future of our AI-powered scientific platform. This position involves designing, constructing, and fine-tuning backend systems that support intelligent, data-centric applications. Your focus will be on creating user interfaces, services, high-performance APIs, and databases while ensuring the robustness of services that merge advanced AI frameworks with intricate scientific analytics and lab workflows.

Collaboration is vital as you'll work alongside ML researchers, platform engineers, and scientists to build systems capable of managing varied workloads and scaling effortlessly. This includes working with structured SQL databases, data lake houses, and vector databases. If you are enthusiastic about crafting high-performance and sophisticated systems, we would love to connect with you!

Your Responsibilities

  • UI and API Development: Create secure, high-performance, and well-documented user interfaces and APIs that integrate seamlessly with AI applications.
  • Database Design and Management: Develop schemas and oversee diverse data systems (including SQL, NoSQL, and Vector DBs) for peak performance and scalability.
  • Application Implementation: Spearhead the development of both front-end and backend services with an emphasis on performance, maintainability, and reliability.
  • System Optimization: Identify and resolve system bottlenecks to ensure high availability and low-latency performance across large-scale workloads.
  • Cloud Services and Infrastructure: Utilize AWS services, Kubernetes, and cutting-edge DevOps practices to design and deploy production-ready systems at scale.
  • Collaborative Development: Partner with ML researchers, engineers, and scientists to weave data pipelines, APIs, and cloud infrastructure into scientific workflows.

About Lila Sciences

At Lila Sciences, we are dedicated to transforming scientific workflows through innovative technology. Our team is passionate about leveraging AI to address complex scientific challenges and drive impactful research.

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