Jobs at Lila Sciences

Design, prototype, and integrate electromechanical systems and robotics subassemblies for lab instrumentation. Collaborate with cross-functional teams, develop firmware and controls, perform testing and debugging, and maintain technical documentation.

Provide high-impact executive support to senior leaders across commercial, product, and corporate development: manage complex calendars, coordinate meetings and materials, track commitments and follow-ups, draft executive communications, and support team operations and onsite logistics.

The VP of Engineering will lead the creation of a unified platform for lab automation, integrating AI for enhanced scientific experimentation, driving engineering initiatives, and mentoring teams across multi-disciplinary domains.

Own a public-sector portfolio (starting with DARPA and ARPA-H), build agency relationships, qualify and prioritize RFIs/RFPs/BAAs, lead opportunities from ID to award and handoff, translate Lila's science into federal narratives, and develop reusable capture playbooks to scale government partnerships and recurring funding.

Own full-cycle recruiting for commercial, corporate development, and G&A roles. Partner with senior leaders to define roles, source and screen candidates, run interview processes, advise on compensation, negotiate and close offers, and improve recruiting process and candidate experience.

Own and grow enterprise accounts in chemicals and materials by prospecting, qualifying, and closing complex R&D-focused deals. Lead cross-functional technical discovery, craft customer-facing materials and proposals, manage forecasts and CRM, and partner with product and science teams to scope high-value engagements and define repeatable GTM playbooks.

Lead program governance and cross-functional coordination for the AISF portfolio. Establish charters, roadmaps, and governance; track milestones, risks, and dependencies; run alignment sessions and executive briefings; coordinate resourcing and budgeting; and implement process improvements to scale program delivery across research, engineering, product, and operations.

Own the roadmap and delivery of fine-tuned Lila model variants and the prioritized backlog of training-capability packages (RL environments and SFT data). Define required training data, evals, release criteria, and coordinate handoffs to app and platform teams. Partner closely with AI Research to translate customer-driven capability requests into executable requirements and integrate into sprint planning to track delivery and unblock dependencies.

Define and validate agent-usable computational biophysics tools and workflows for drug discovery. Design, parameterize, and benchmark molecular simulation and binding free-energy (RBFE/ABFE) pipelines, establish QC standards, integrate open-source tools (e.g., OpenMM/OpenFE), identify failure modes, and partner with ML and engineering teams to turn validated protocols into scalable, reproducible APIs and agent-invokable tooling.

Turn research prototypes into scalable, fault-tolerant ML and physics infrastructure for drug discovery. Improve GPU utilization, distributed execution, reproducibility, orchestration, monitoring, and packaging so scientists can run reliable, multi-cluster workflows and agent-usable pipelines.

The role involves researching and developing training strategies for large language models, focusing on their applications in scientific reasoning and performance evaluation.

Design and maintain large-scale distributed training systems, optimize performance for ML models, and improve training efficiency.

Design and build Machine Learning libraries, implement CI/CD pipelines, and support Ray-based compute environments, collaborating with ML experts.

As a Senior Accountant, you will oversee accounting functions, ensure compliance with US GAAP, support audits, and drive process improvements.

As an ML Research Scientist, you will develop AI systems for multimodal data extraction and advance scientific knowledge structuring across domains.

As a Forward Deployed Engineer, you will build and adapt computational tools for scientific data, create data pipelines, and interface directly with clients to deliver impactful AI-driven solutions.

The Staff Forward Deployed Engineer role involves deploying AI-powered engineering solutions in chemistry and materials science, focusing on data workflows and user interfaces to transform scientific discoveries.

Lead synthesis and optimization of single-crystal epitaxial thin films and heterostructures using MBE, PLD, and sputtering. Design and perform structural (XRD, AFM, RHEED) and electronic/magneto-transport (cryogenic resistivity, Hall, magnetoresistance) measurements, maintain UHV deposition equipment, and collaborate with systems and ML teams to enable high-throughput autonomous materials discovery.

As a Senior Software Engineer, focus on backend development and AI integration for scientific applications, building systems that leverage advanced AI techniques.

Lead research on multi-modal reasoning systems, develop training strategies, build datasets, and collaborate with scientists to produce scientific superintelligence.