Modal·San Francisco·5 дн назад
Inference Engineering and Product Lead
Ориентир по рынку≈ 1 490 000 – 1 875 000 ₽наша приблизительная оценка по 41 вакансии этой роли и грейда, у работодателя вилка не указана
🏢 ОфисLeadПолная занятость
Вилки нет, про деньги придётся договариваться с нуля.
Вакансия на английскомПереведёт заголовок и описание вакансии на русский
Наша компания
AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable Ramp Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
Чем предстоит заниматься
Modal's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate
We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area
This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, frontier inference serving, and performance optimization
Drive technical and product decisions through design reviews, code reviews, and architectural discussions
Lead our efforts working with customers with novel or frontier workloads so they can be successful running on Modal
Translate learnings from frontier customers into a roadmap for our internal optimization platform and user-facing product, so that gains from optimization and research efforts are accessible to all of our users
Establish standards for reliability and product excellence; ensure the team owns projects end-to-end, from spec through production
Наши требования
10+ years of industry experience, including 3+ years in a leadership role
Track record building high-performance systems at scale
Strong background in cloud infrastructure
Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.)
Experience working with LLM inference in production and familiarity with underlying concepts like engines, kernels, routing, KV cache management and speculative decoding
Дополнительно
Recruit, hire, and grow a high-performing team of engineers; run regular 1:1s focused on coaching, feedback, and career growth
Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work
Foster a culture of ownership, accountability, customer obsession, and continuous improvement
Partner with business operations and compute strategy on continuing to develop our strategy for compute purchases across a variety of accelerators
Collaborate with GTM on product launches, positioning, and improving win rates for inference opportunities
Help guide the roadmap for teams building the infrastructure platform underlying inference, as well as adjacent product teams