Your Impact at LILA

Lila is hiring an Associate Director/Director, Inference Engineering to lead the team responsible for Lila's model serving platform: the inference APIs, serving frameworks, request routing, batching strategies, and deployment systems that bring models reliably to production.

You will define how Lila serves models at scale, balancing latency, throughput, quality, and cost, and act as the technical authority connecting research and ML to production-grade serving capabilities. The work spans people leadership, service ownership, cross-functional partnership, and deep technical judgment in modern LLM serving.

What You'll Be Building

Own the inference service end to end: API contracts, latency SLAs, throughput guarantees, rate limits
Drive serving architecture decisions: batching, KV cache, speculative decoding, quantization, multi-node deployment
Establish SLOs for latency, throughput, and availability, plus 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

What You'll Need to Succeed

Deep understanding of the inference stack for large language models, including serving frameworks (e.g., vLLM, TensorRT-LLM, 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 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

Bonus Points For

Hands-on experience with speculative decoding, quantization (AWQ, GPTQ, FP8), or model parallelism strategies
Experience with serving evaluation: 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

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range

$204,000—$348,000 USD

About LILA

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. 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. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.