Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Lila Sciences is seeking a Research Engineer, Scientific Computing and ML/Physics Infrastructure to help turn promising research tools into robust, scalable systems. This role bridges research and production, working with scientists and ML researchers to make their tools efficient, distributed, fault tolerant, and usable across Lila's compute environments. The Molecular Intelligence team is building ML and physics-based infrastructure for drug discovery, including biophysics workflows, computational chemistry tools, cofolding models, low-data learning systems, simulation workflows, and agent-usable scientific pipelines. The ideal candidate will improve code quality, architecture, GPU efficiency, cluster portability, and operational reliability without slowing down research velocity.

Responsibilities

Take research tools, prototypes, and scientific workflows developed by scientists or academic-style researchers and make them scalable, efficient, and maintainable.
Collaborate directly with computational biophysics, computational chemistry, and machine learning scientists to turn research workflows into scalable agent-usable systems.
Build and support ML and physics infrastructure for model training, molecular simulation, data processing, and agent-executed scientific workflows.
Ensure workflows run reliably across multiple clusters and compute environments.
Improve GPU utilization, distributed execution, throughput, fault tolerance, and reproducibility for ML and scientific workloads.
Architect larger-scale systems around research code, including job orchestration, retry behavior, monitoring, artifact handling, and workflow traceability.
Optimize ML, physics, and pipeline code for performance and scalability.
Maintain development and execution environments across local, cloud, and GPU-based systems.
Package scientific tools into reusable services, workflows, or APIs that can be used by researchers, pipelines, and AI agents.
Partner with research, platform, and infrastructure teams to bridge exploratory scientific work with reliable engineering systems.
Document systems clearly and establish pragmatic engineering patterns for research teams.

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.
Practical knowledge of Linux, Docker or containers, dependency management, and reproducible development environments.
Experience with orchestration, scheduling, or distributed execution systems such as Kubernetes, Slurm, Ray, Flyte, Argo, or similar tools.
Ability to take prototype-quality research code and improve its architecture, scalability, reliability, and maintainability.
Strong debugging skills across code, environments, infrastructure, data pipelines, and compute clusters.
Ability to work directly with researchers, understand ambiguous technical needs, and convert them into robust engineering solutions.

Skills

Python
ML
Scientific Computing
Simulation
GPU Computing
Performance Profiling
Distributed Execution
PyTorch
JAX
CUDA-aware workflows
Linux
Docker
Dependency Management
Kubernetes
Slurm
Ray
Flyte
Argo
Debugging
Chemistry
Computational Biophysics
Molecular Simulation
Computational Chemistry
Cheminformatics
Drug Discovery
Cloud GPU Infrastructure
Multi-cluster Execution
Hybrid Compute Environments
LLM Agents
Automated Research Workflows
Workflow Observability
Checkpointing
Retries
Fault-tolerant Scientific Workloads
CI
Testing
Packaging
Release Practices
Research Software Support

Location

U.S.

Work Type

Full-time

Experience Level

Senior

Salary/Compensations

$224,000—$294,000 USD

Benefits

Medical, dental, and vision coverage
Employer-paid life and disability insurance
Flexible time off with generous company wide holidays
Paid parental leave
Educational assistance program
Commuter benefits, including bike share memberships for office based employees
Company subsidized lunch program
International benefits tailored to region

About the Company

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.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

Equal Opportunity

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.