Senior Machine Learning Engineer, Physical Sciences

Lila Sciences
Cambridge
Workplace: OnsiteFull timeUSD 128,000 - 198,000 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Python","PyTorch","Huggingface","FastAPI","GRPC","Docker","Kubernetes","CI/CD","LLMs","RAG","Debugging","Profiling","Testing","Documentation","Communication"]

Build and operate end-to-end, scalable machine learning workflows for materials, chemistry and physical sciences. Design and productionize models with CI/CD, collaborate with domain scientists and software engineers, and mentor best practices to enable rapid, safe releases of ML-powered solutions.

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Lila Sciences
Lila Sciences
7 months ago

Senior Machine Learning Engineer, Physical Sciences

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Last checked: 32 minutes agoStatus: Live

Job Summary

Build and operate end-to-end, scalable machine learning workflows for materials, chemistry and physical sciences. Design and productionize models with CI/CD, collaborate with domain scientists and software engineers, and mentor best practices to enable rapid, safe releases of ML-powered solutions.
Location: Cambridge
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, implement, and maintain end‑to‑end ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
  • •Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
  • •Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
  • •Contribute to technical design reviews, coding standards, and mentoring of best practices.

Pay and Benefits

Salary: USD 128,000 - 198,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401kEquityCommuter BenefitsMeal Allowance

Key Requirements

  • •BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
  • •Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
  • •Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
  • •Hands‑on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
  • •Clear communication and collaboration in cross‑functional settings.
Experience:Physical sciencesMaterialsChemistryAI/ML
Education:Bachelor's
Skills:PythonPyTorchHuggingfaceFastAPIGRPCDockerKubernetesCI/CDLLMsRAGDebuggingProfilingTestingDocumentationCommunication
Languages:English
Tech Stack:PythonPyTorchHuggingfaceFastAPIGRPCDockerKubernetesCI/CDLLMsRAG

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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