Co-op, Software, Applied AI Platform Engineer

Lila Sciences
Lila Sciences logo
Location
San Francisco, CA USA
Job Type
Full-time
Posted
November 11, 2026

Job Description

Your Impact at LILA

Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. The Platform Engineering team owns the core infrastructure and developer-facing services that power Lila's AI Science Factory™ — including APIs, data pipelines, and the agentic systems that orchestrate scientific workflows at scale.

This co-op has two focus tracks. Candidates may be matched to one or both based on interest and fit:

Track 1 — Data Platform:Build pipelines and services that structure scientific knowledge (literature, patents, lab data) into signals that power Lila's AI models and applications.

Track 2 — Agentic SSR (AI and Server-Side Rendering):Build the server-rendered, agentic layer of the Lila Platform — the infrastructure that enables AI agents to compose and serve dynamic scientific interfaces at runtime.

In either track, you will ship production code, work alongside research scientists and ML engineers, and contribute to a platform that runs real scientific experiments.

What You'll Be Building

Data Platform Track

  • Build and maintain ingestion and transformation pipelines for scientific literature, patents, and lab-generated data
  • Implement structured data extraction workflows, including schema design, validation, and quality evaluation
  • Integrate retrieval and RAG pipelines that surface relevant documents, tables, and figures to downstream Lila applications
  • Generate and validate structured datasets; run end-to-end pipelines and analyze results against clear evaluation criteria
  • Collaborate with research scientists to translate scientific domain requirements into robust data models
  • Document findings and present results to the team; contribute to a publication or open-source project where the work supports it

Agentic SSR Track

  • Build server-side rendering services and APIs that enable AI agents to compose and deliver dynamic scientific interfaces
  • Implement agentic workflow primitives: task routing, context management, streaming responses, and tool integration
  • Develop platform features end-to-end: schema design, business logic, API surface, and automated tests
  • Instrument code for observability; participate in debugging and root-cause analysis of production issues
  • Improve developer experience through internal tooling, reusable libraries, and documentation
  • Contribute to technical design discussions and code reviews

What You'll Need to Succeed

  • Pursuing a Bachelor's, Master's, or PhD in Computer Science, Software Engineering, or a related field
  • Strong foundation in software engineering fundamentals: data structures, algorithms, and system design
  • Proficiency in Python and/or TypeScript
  • Experience building or consuming REST or GraphQL APIs
  • Familiarity with relational databases and SQL
  • Ability to work independently, take ownership of tasks, and communicate progress clearly
  • Curiosity about scientific data or AI-driven software systems and a willingness to learn quickly

Bonus Points For

Data Platform Track

  • Familiarity with NLP, document understanding (OCR, table/figure extraction), or multimodal models
  • Experience with LLM applications, embeddings, or retrieval systems (chunking, reranking, vector search)
  • Experience building evaluation sets, annotation workflows, or working with messy real-world data
  • Interest in scientific document parsing or knowledge graph construction

Agentic SSR Track

  • Experience with server-side rendering frameworks (Next.js, Remix, or similar)
  • Exposure to LLM APIs, agentic frameworks (LangChain, LangGraph, or similar), or AI-assisted developer tooling
  • Experience with cloud infrastructure (AWS, GCP, or Azure) or containerized environments (Docker, Kubernetes)
  • Familiarity with event-driven architectures or message queues (Kafka, Pub/Sub, SQS)

Both Tracks

  • Experience contributing to or maintaining open-source projects
  • Prior internship or co-op experience in a software engineering role

About LILA

Your Impact at LILA

Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. The Platform Engineering team owns the core infrastructure and developer-facing services that power Lila's AI Science Factory™ — including APIs, data pipelines, and the agentic systems that orchestrate scientific workflows at scale.

This co-op has two focus tracks. Candidates may be matched to one or both based on interest and fit:

Track 1 — Data Platform:Build pipelines and services that structure scientific knowledge (literature, patents, lab data) into signals that power Lila's AI models and applications.

Track 2 — Agentic SSR (AI and Server-Side Rendering):Build the server-rendered, agentic layer of the Lila Platform — the infrastructure that enables AI agents to compose and serve dynamic scientific interfaces at runtime.

In either track, you will ship production code, work alongside research scientists and ML engineers, and contribute to a platform that runs real scientific experiments.

What You'll Be Building

Data Platform Track

  • Build and maintain ingestion and transformation pipelines for scientific literature, patents, and lab-generated data
  • Implement structured data extraction workflows, including schema design, validation, and quality evaluation
  • Integrate retrieval and RAG pipelines that surface relevant documents, tables, and figures to downstream Lila applications
  • Generate and validate structured datasets; run end-to-end pipelines and analyze results against clear evaluation criteria
  • Collaborate with research scientists to translate scientific domain requirements into robust data models
  • Document findings and present results to the team; contribute to a publication or open-source project where the work supports it

Agentic SSR Track

  • Build server-side rendering services and APIs that enable AI agents to compose and deliver dynamic scientific interfaces
  • Implement agentic workflow primitives: task routing, context management, streaming responses, and tool integration
  • Develop platform features end-to-end: schema design, business logic, API surface, and automated tests
  • Instrument code for observability; participate in debugging and root-cause analysis of production issues
  • Improve developer experience through internal tooling, reusable libraries, and documentation
  • Contribute to technical design discussions and code reviews

What You'll Need to Succeed

  • Pursuing a Bachelor's, Master's, or PhD in Computer Science, Software Engineering, or a related field
  • Strong foundation in software engineering fundamentals: data structures, algorithms, and system design
  • Proficiency in Python and/or TypeScript
  • Experience building or consuming REST or GraphQL APIs
  • Familiarity with relational databases and SQL
  • Ability to work independently, take ownership of tasks, and communicate progress clearly
  • Curiosity about scientific data or AI-driven software systems and a willingness to learn quickly

Bonus Points For

Data Platform Track

  • Familiarity with NLP, document understanding (OCR, table/figure extraction), or multimodal models
  • Experience with LLM applications, embeddings, or retrieval systems (chunking, reranking, vector search)
  • Experience building evaluation sets, annotation workflows, or working with messy real-world data
  • Interest in scientific document parsing or knowledge graph construction

Agentic SSR Track

  • Experience with server-side rendering frameworks (Next.js, Remix, or similar)
  • Exposure to LLM APIs, agentic frameworks (LangChain, LangGraph, or similar), or AI-assisted developer tooling
  • Experience with cloud infrastructure (AWS, GCP, or Azure) or containerized environments (Docker, Kubernetes)
  • Familiarity with event-driven architectures or message queues (Kafka, Pub/Sub, SQS)

Both Tracks

  • Experience contributing to or maintaining open-source projects
  • Prior internship or co-op experience in a software engineering role

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

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.

Information you provide during your application process will be handled in accordance with ourCandidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

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Frequently Asked Questions

Where is this co-op located, and is it remote, hybrid, or on-site?
The position is located in San Francisco, CA, USA. The posting does not specify whether the role is remote, hybrid, or on-site.
What qualifications do I need for this co-op?
You should be pursuing a Bachelor's, Master's, or PhD in Computer Science, Software Engineering, or a related field. You'll also need strong software engineering fundamentals, proficiency in Python and/or TypeScript, experience with REST or GraphQL APIs, and familiarity with relational databases and SQL.
What are the focus tracks for this co-op?
There are two tracks. Data Platform focuses on pipelines that structure scientific literature, patents, and lab data. Agentic SSR focuses on server-side rendering services that let AI agents compose and serve dynamic scientific interfaces. Candidates may be matched to one or both tracks based on interest and fit.
What will I be working on day to day?
You will ship production code in either track. Data Platform work includes ingestion pipelines, structured data extraction, and RAG integration. Agentic SSR work includes SSR services and APIs, agentic workflow primitives, observability, internal tooling, and code reviews.
Who will I be working with?
You'll join the Platform Engineering team, which owns Lila's core infrastructure and developer-facing services. You'll work alongside research scientists and ML engineers.
What experience would give me an edge?
For Data Platform: NLP, document understanding, LLM/retrieval systems, or evaluation sets. For Agentic SSR: Next.js/Remix, LLM APIs or agentic frameworks, cloud or containers, or message queues. For both tracks: open-source contributions or prior software internship or co-op experience.
Should I apply if I don't meet every qualification?
Yes. Lila encourages candidates to apply even if they don't meet every listed qualification.

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Job Information

Source: manual
AI Relevance: 75/100 (Relevant)
Remote Type: onsite
Skills & Tags:
lila sciences NLP LLM
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