Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure

About the role

Lila Sciences is seeking a Research Engineer in Scientific Computing and ML/Physics Infrastructure to bridge research and production. You will collaborate with scientists and ML researchers to transform promising research tools into robust, scalable systems. The Molecular Intelligence team focuses on 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. This role requires improving code quality, architecture, GPU efficiency, cluster portability, and operational reliability while maintaining 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 for 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

• Familiarity with chemistry, computational biophysics, molecular simulation, computational chemistry, cheminformatics, or drug discovery workflows.
• Experience with cloud GPU infrastructure, multi-cluster execution, or hybrid compute environments.
• Experience building tools for LLM agents or automated research workflows.
• Experience with workflow observability, checkpointing, retries, and fault-tolerant scientific workloads.
• Experience with CI, testing, packaging, and release practices for research software.
• Comfort supporting fast-moving research teams without over-engineering exploratory work.

Benefits

• Comprehensive 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.

Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.

Pay

Expected Base Salary Range: $224,000 USD - $294,000 USD (U.S.-based positions; international salaries are set to local market). Competitive base compensation with bonus potential and generous early-stage equity.

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. 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.