Associate Director/Director, Inference Engineering

Lila Sciences • San Francisco, MA

1d

About The Position

Lila Sciences is hiring an Associate Director/Director, Inference Engineering to lead the team responsible for its model-serving platform, including inference APIs, serving frameworks, request routing, batching strategies, and deployment systems. The role defines how Lila serves models at scale while balancing latency, throughput, quality, and cost, and serves as the technical authority connecting research and machine learning to production-grade serving capabilities. The work combines people leadership, service ownership, cross-functional partnership, and technical judgment in modern large language model serving.

The successful candidate will own the inference service and its roadmap, establish serving architecture and reliability practices, and partner with ML, research, and product engineering to bring new models into production. They will build, mentor, and retain a high-performing engineering team.

Lila Sciences is building Scientific Superintelligence™ to accelerate scientific discovery across medicine, materials, and energy. It combines advanced AI models with proprietary AI Science Factory™ instruments in an operating system designed to execute the scientific method autonomously. The company emphasizes truth, trust, curiosity, grit, and velocity, and is committed to equal employment opportunity.

The expected U.S. base salary range is $204,000–$348,000, with bonus potential and early-stage equity. Final offers reflect background, expertise, and expected impact. Full-time U.S. employees receive medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off and company-wide holidays; paid parental leave; educational assistance; commuter benefits, including bike share memberships for office-based employees; and a subsidized lunch program. Benefits for employees outside the U.S. are tailored to their region.

Requirements

• Deep understanding of the large language model inference stack, including serving frameworks such as vLLM, TensorRT-LLM, and TGI; batching strategies; memory constraints; and latency/throughput tradeoffs.
• Experience owning a customer- or product-facing API service end to end, including SLAs, incident response, and service reliability in fast-moving environments.
• Track record of hiring, mentoring, and retaining senior technical talent and scaling engineering organizations through rapid growth.
• Strong technical judgment across latency, throughput, reliability, cost, and delivery speed.
• Demonstrated ability to set technical strategy and execute as priorities change.
• Ability to align ML, research, product engineering, and executive stakeholders with competing priorities.

Nice To Haves

• Hands-on experience with speculative decoding, quantization (AWQ, GPTQ, FP8), or model parallelism strategies.
• Experience with serving evaluation, including output quality regression testing, A/B routing, and shadow deployments.
• Familiarity with GPU capacity planning, instance provisioning, utilization, and cloud cost modeling.
• Prior work in AI/ML startups or research-heavy organizations.

Responsibilities

• Own the inference service end to end, including API contracts, latency SLAs, throughput guarantees, and rate limits.
• Drive serving architecture decisions involving batching, KV cache, speculative decoding, quantization, and multi-node deployment.
• Establish SLOs for latency, throughput, and availability, as well as on-call and postmortem practices.
• Partner with ML, research, and product engineering to make new models production-ready.
• Build systems for model onboarding, deployment safety, evaluation gates, and observability.
• Build, mentor, and retain a high-performing engineering team, and own the serving roadmap.

Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• Medical, dental, and vision coverage for full-time U.S. employees.
• Employer-paid life and disability insurance for full-time U.S. employees.
• Flexible time off and generous company-wide holidays.
• Paid parental leave.
• Educational assistance program.
• Commuter benefits, including bike share memberships for office-based employees.
• Company-subsidized lunch program.
• Regionally tailored comprehensive benefits for full-time employees outside the U.S.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed