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Lila Sciences

AI-powered scientific discovery for medicines

Staff Forward Deployed Engineer - Life Sciences

AI Application Engineering +1Confirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Background in biology, molecular science, or a related scientific field.
  • Experience with data engineering, ETL pipelines, and working with complex datasets.
  • Strong full-stack development skills across backend, frontend, and data layers.
  • Willingness to travel to customer sites for engineering deployments.

Responsibilities

  • Embed directly within internal and external customer-facing biotech and science teams to understand their problems and rapidly ideate, build, and deploy solutions using the Lila platform.
  • Develop, wrap, and adapt domain-specific tools for molecular modeling, data analysis, process optimization, and related work.
  • Deploy custom agentic scientific workflows that integrate with industrial instruments, including PLCs and control software, and data systems, including ERP, MES, and SCADA.
  • Build real-time data pipelines that transform scientific data into actionable insights.
  • Create intuitive interfaces that make complex AI/ML capabilities accessible to scientists.
  • Develop custom features that address each customer's unique challenges.
  • Identify customer requirements and communicate well-defined requirements to product teams.

Desired Qualifications

  • Previous customer-facing or consulting experience.
  • Depth in controls engineering and machine learning.
  • Experience with scientific computing libraries, including NumPy, Pandas, SciPy, and RDKit.
  • Familiarity with machine learning/artificial intelligence implementation and deployment.
  • Familiarity with modern web technologies, including TypeScript and React.

About the Company

Lila Sciences

AI-powered scientific discovery for medicines

Lila.ai uses artificial intelligence to speed up scientific discovery in medicines and advanced materials. The system ingests large sets of scientific data, experimental results, and literature to identify patterns, generate hypotheses, and guide research programs. It differentiates itself by tackling deep scientific problems at scale and combining AI with domain expertise, rather than offering generic tools. The goal is to help humanity by delivering new medicines and materials that solve major biological and materials challenges through data-driven discovery.

Company size
501-1,000
Company stage
Series A
Total funding
$550M
Headquarters
Cambridge, MA
Founded
2024

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