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Led Engineer Jobs in California (NOW HIRING)

Built or led engineering teams working directly on GPU or accelerator-level inference performance, ML compilers, kernels, runtimes, or hardware-software co-design. * Contributed to or led teams ...

Head of Engineering

San Francisco, CA · On-site

$260 - $380/hr

Built or led engineering teams working directly on GPU or accelerator-level inference performance, ML compilers, kernels, runtimes, or hardware-software co-design. * Contributed to or led teams ...

Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with * Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg.

Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with * Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg, TypeScript. Benefits * Unlimited ...

Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with * Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS. Benefits * Unlimited PTO.

Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with * Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS. Benefits * Unlimited PTO.

New

Full Stack Engineer

San Francisco, CA · On-site

$165K - $225K/yr

Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with * Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg.

Full Stack Engineer

San Francisco, CA · On-site

$140 - $210/hr

Mentored colleagues or led engineering initiatives. * Developed or improved design systems. * Interest in AI, digital platforms, or automation. * Open-source contributions or personal projects.

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Principal Software Engineer

Palo Alto, CA · On-site

$158K - $212K/yr

You have led engineers across both machine learning and infrastructure * You have experience with GPU systems, distributed systems, Kubernetes, AWS, MLOps, or production computer vision * You have ...

You have led engineers across both machine learning and infrastructure * You have experience with GPU systems, distributed systems, Kubernetes, AWS, MLOps, or production computer vision * You have ...

Principal Software Engineer

Palo Alto, CA · On-site

$300K - $600K/yr

You have led engineers across both machine learning and infrastructure * You have experience with GPU systems, distributed systems, Kubernetes, AWS, MLOps, or production computer vision * You have ...

You've led engineering teams shipping production systems and have strong people leadership and coaching skills. * You can align research, product, data, and infrastructure on what "good" means--and ...

New

Head of Swarms Cloud

Palo Alto, CA · On-site

$180 - $250/hr

You have led engineering teams and shipped platforms developers depend on * You care about developer experience as much as system design * You want to build the infrastructure that autonomous ...

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Showing results 1-20

Led Engineer information

What does a led engineer do?

A LED Engineer specializes in the design, development, and optimization of LED lighting systems. They work on circuit design, thermal management, and energy efficiency to create high-performance lighting solutions. Additionally, they collaborate with manufacturing teams to ensure product reliability and compliance with industry standards.

What are the key skills and qualifications needed to thrive as a led engineer?

To excel as an LED Engineer, you should have a strong background in electrical or electronics engineering, circuit design, and knowledge of LED lighting systems, ideally supported by a relevant degree. Familiarity with CAD design software, PCB layout tools, and industry certifications such as IPC or similar are commonly required. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills will help you stand out. These competencies are vital to ensure the efficient design, implementation, and coordination of advanced LED systems in various real-world applications.

What are the most commonly searched types of Led Engineer jobs in California?

The most popular types of Led Engineer jobs in California are:

What job categories do people searching Led Engineer jobs in California look for?

The top searched job categories for Led Engineer jobs in California are:

What cities in California are hiring for Led Engineer jobs?

Cities in California with the most Led Engineer job openings:

Infographic showing various Led Engineer job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 90% In-person, and 10% Remote job distribution.

Head of Engineering

Inferact

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 15 days ago


Job description

Overview
Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.
About the Role
We're looking for a Head of Engineering to build and lead the organization developing the systems that power vLLM and Inferact. This role requires an engineering leader with genuine technical credibility at the inference layer-someone who understands GPU and accelerator performance, inference runtimes, ML systems optimization, and hardware-software co-design deeply enough to earn the trust of exceptional staff-level engineers.
You'll partner closely with the founders to scale a senior-heavy, highly specialized engineering team while preserving the technical rigor, speed, and ownership that made vLLM successful. You'll recruit and develop rare ML systems talent, translate ambitious research and infrastructure work into a focused execution plan, strengthen how teams operate, and help Inferact deliver reliable, high-performance inference across models, hardware, and deployment environments.
Skills and Qualifications
Minimum qualifications:
  • Bachelor's degree or equivalent experience in computer science, engineering, machine learning, systems, or a related field.
  • Engineering leadership experience building and scaling highly specialized teams in LLM inference, ML systems, GPU or accelerator software, distributed systems, or closely related infrastructure.
  • Deep technical credibility at the inference layer, including hands-on understanding of inference runtimes, GPU or accelerator optimization, kernels, memory and communication bottlenecks, and hardware-software tradeoffs.
  • Ability to distinguish core inference-engine work from the routing, orchestration, and application layers above it, with opinions grounded in direct technical experience.
  • A strong record of recruiting, assessing, and retaining senior engineers, staff-level ICs, PhDs, and research-adjacent engineers in a production engineering environment.
  • Experience translating technically ambitious work into clear priorities, accountable ownership, execution plans, and durable engineering operating mechanisms.
  • Ability to remain close enough to the work to identify risks, pattern-match on difficult technical problems, and unblock teams without becoming a bottleneck or displacing technical ownership.

Preferred qualifications:
  • Experience leading teams responsible for LLM serving, vLLM, SGLang, model execution, inference performance, GPU kernels, compiler or runtime systems, or distributed AI infrastructure.
  • Experience scaling a small, senior-heavy engineering organization where the relevant talent market is narrow and technical quality matters more than headcount growth.
  • Experience integrating research-oriented or PhD talent into production teams, including setting expectations, structuring work, and building effective collaboration with product-focused engineers.
  • Strong judgment across organizational design, hiring, performance management, technical planning, execution cadence, and cross-functional decision-making.
  • Ability to represent the engineering organization credibly with open-source contributors, hardware partners, cloud providers, customers, candidates, and investors.

Bonus points if you have:
  • Built or led engineering teams working directly on GPU or accelerator-level inference performance, ML compilers, kernels, runtimes, or hardware-software co-design.
  • Contributed to or led teams around open-source ML systems projects such as vLLM, SGLang, PyTorch, Ray, Triton, XLA, ROCm, or related infrastructure.
  • Scaled an engineering organization through an inflection point while preserving high technical standards, fast iteration, and direct ownership.
  • Recruited successfully from a global, highly competitive ML systems talent pool and built relationships with technical communities beyond traditional candidate pipelines.
  • Led engineering in an early-stage AI infrastructure, developer infrastructure, distributed systems, or open-source company.

Logistics
  • Location: This role is based in San Francisco, California. Will consider relocation for exceptional candidates.
  • Compensation: Compensation will be determined based on background, skills, and experience. Offer will include a highly competitive base and meaningful equity.
  • Visa sponsorship: We sponsor visas on a case-by-case basis.
  • Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.