Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure

Lila Sciences
Cambridge, London, San Francisco
Workplace: OnsiteFull timeUSD 224,000 - 294,000Function: Research & Scientific (R&D)Skills: ["Collaboration","Debugging","Problem-solving","Communication","Stakeholder management"]

Turn research prototypes in molecular intelligence into scalable, efficient, and maintainable systems for drug discovery. Build ML and physics infrastructure for model training, simulation, data processing, and agent-executed scientific workflows that run reliably across multiple clusters. Improve GPU utilization, distributed execution, fault tolerance, reproducibility, and job orchestration (retries, monitoring, artifact handling, traceability), while partnering with researchers and infrastructure teams.

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Lila Sciences
Lila Sciences
3 days ago

Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live

Job Summary

Turn research prototypes in molecular intelligence into scalable, efficient, and maintainable systems for drug discovery. Build ML and physics infrastructure for model training, simulation, data processing, and agent-executed scientific workflows that run reliably across multiple clusters. Improve GPU utilization, distributed execution, fault tolerance, reproducibility, and job orchestration (retries, monitoring, artifact handling, traceability), while partnering with researchers and infrastructure teams.
Location: Cambridge, London, San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Scale research tools, prototypes, and scientific workflows into efficient, maintainable systems.
  • •Collaborate with computational biophysics, computational chemistry, and machine learning scientists to create agent-usable scalable workflows.
  • •Build and support ML/physics infrastructure for model training, molecular simulation, data processing, and agent-executed scientific workflows.
  • •Ensure workflows run reliably across multiple clusters and compute environments, improving fault tolerance and reproducibility.
  • •Architect larger-scale systems around research code, including job orchestration, retry behavior, monitoring, artifact handling, and workflow traceability.

Pay and Benefits

Salary: USD 224,000 - 294,000
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalRemote WorkMeal Allowance

Key Requirements

  • •Strong software engineering skills in Python and experience working with ML, scientific computing, or simulation codebases.
  • •Experience building, scaling, or operating distributed systems for research, ML, physics, simulation, or data-intensive workloads.
  • •Practical knowledge of GPU computing, performance profiling, distributed execution, and failure modes in large-scale workloads.
  • •Experience with PyTorch, JAX, CUDA-aware workflows, or related ML/scientific computing frameworks.
  • •Experience with Linux and Docker/containers, dependency management, reproducible development environments, and orchestration/scheduling systems such as Kubernetes, Slurm, Ray, Flyte, or Argo.
Skills:CollaborationDebuggingProblem-solvingCommunicationStakeholder management
Languages:English
Tech Stack:PythonPyTorchJAXCUDALinuxDockerContainersKubernetesSlurmRayFlyteArgoGPUDistributed systems

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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