Associate Director/Director, Inference Engineering
Lila Sciences
$204,000 - $348,000 / year
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Description
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.
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.
We’re All In
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.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Benefits
- health insurance
- vision insurance
- stock options
- parental leave
- disability insurance
About this role
Lila Sciences is looking for a leader to own the inference engineering function—the systems that bring language models reliably into production at scale. You'll define serving architecture decisions around batching, memory management, and multi-node deployment; establish SLOs for latency, throughput, and availability; and act as the technical authority bridging research, ML, and product teams. The role demands both deep technical judgment on modern LLM serving frameworks and the ability to set strategy as priorities shift in a fast-moving environment.
This is a people leadership position as much as a technical one. You'll build and mentor a high-performing team, own the serving roadmap, and navigate competing priorities across ML, research, product engineering, and executive stakeholders. Success requires a track record of owning customer-facing API services end to end—including incident response and reliability practices—plus demonstrated ability to hire and scale engineering organizations through growth.
The ideal candidate has hands-on depth in the inference stack: familiarity with vLLM, TensorRT-LLM, or similar frameworks; understanding of batching strategies and latency/throughput tradeoffs; and ideally exposure to speculative decoding, quantization techniques, or model parallelism. Experience in AI/ML startups or research-heavy organizations is a plus. The role is full-time, in-office in Cambridge, MA, with a base salary range of $204,000–$348,000 plus bonus and early-stage equity.
How this employer is doing
solid
- H1B: Sponsors Visas
- Recently Raised Funding
- Sponsors Visas
In the news
Lila Sciences in talks for $2B funding at $8.5B valuation - Bloomberg, Investing.com
This role's local market on JobMinglr
Pay for this role
$204,000 to $348,000 per year
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