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Senior Software Engineer in Applied AI

Lila SciencesCambridge, MA USA
On-site Full-time $148K/yr - $210K/yr

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Experience Level

Senior

Qualifications

Qualifications for Success Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Experience: A minimum of 7 years of professional experience in developing and scaling production systems, including advanced knowledge in backend development and AI integrations.

About the job

Your Role at Lila Sciences

We are in search of a Senior Software Engineer to become a pivotal member of our Applied AI team, contributing to the development of our next-generation AI-powered scientific platform. This position involves designing and refining backend systems, data pipelines, and AI integrations that facilitate intelligent, data-centric applications. You will operate at the crossroads of backend engineering and machine learning, ensuring that our platform scales effectively and supports state-of-the-art applied AI methodologies such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration.

This opportunity is perfect for individuals who excel at merging software engineering with applied AI, transforming research into production-level systems that foster genuine scientific breakthroughs. If you are driven by the challenge of building high-performing, sophisticated systems that maximize the utility and impact of AI, we would be eager to connect with you!

Your Contributions

  • Applied AI Integration: Design and implement backend services and data pipelines that underpin advanced AI applications, including LLMs, RAG, and agentic frameworks.
  • API & Service Development: Create high-performance APIs and microservices that facilitate seamless interactions between AI models, scientific tools, and user-facing applications.
  • Data Pipeline Architecture: Architect and oversee scalable pipelines adept at managing structured, unstructured, and vectorized data for AI/ML workloads.
  • Database & Knowledge Systems: Develop and optimize SQL, NoSQL, and vector databases to ensure low-latency AI retrieval and inference tasks.
  • Cloud & Infrastructure: Utilize AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to construct resilient, production-ready AI platforms.
  • Performance & Reliability: Identify system bottlenecks, optimize for efficiency and speed, and guarantee the reliability and fault-tolerance of AI-driven processes.
  • Collaboration: Work closely with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready solutions.

About Lila Sciences

Lila Sciences is at the forefront of scientific innovation, dedicated to harnessing the power of artificial intelligence to revolutionize research and discovery within the life sciences sector.

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