Efficiency Engineer Jobs in California
Efficiency Engineer jobs in California are in steady demand, concentrated in aerospace and defense manufacturing, semiconductors and clean technology, and large-scale logistics and utilities operations, with openings at every level from entry-level process analyst through senior continuous improvement lead. The largest hiring activity is centered in Los Angeles, the San Francisco Bay Area, and San Diego, where employers such as Northrop Grumman, Chevron, and Applied Materials maintain established operations. Lean manufacturing, energy efficiency compliance under California regulatory frameworks, and supply chain optimization are the most consistently sought specialties. Find a role that fits below and apply directly.
Find Efficiency Engineer JobsOverview
Showing 5 of 16+ Efficiency Engineer jobs
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience programming in C++ or Python.
- 2 years of experience with software design and architecture.
- 2 years of experience testing, and launching software products.
- Experience with ML model optimization.
- Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience with debugging correctness and performance issues at all levels of the ML software stack.
- Experience with ML compilers and their internals, experience writing compiler optimization passes.
- Familiarity with accelerator hardware architectures (TPUs/GPUs).
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
On this team, you will own the optimization of the models powering the YouTube algorithm. Your work will focus on model efficiency optimization, such as low-precision quantization , knowledge distillation, parameter sharing, and designing hardware-friendly model architectures, to reduce training and serving costs while maximizing fleet utilization and value delivered to users.
You will build support and optimize new and existing models in our Recommendation System stack, including new model architectures while adapting to next-generation TPU hardware.
You will engage in model and TPU compiler co-design, with opportunities to work across the stack ranging from end-user ML models down to Hardware/Software architecture.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Profile ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
- Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
- Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
- Partner closely with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience programming in C++ or Python.
- 2 years of experience with software design and architecture.
- 2 years of experience testing, and launching software products.
- Experience with ML model optimization.
- Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience with debugging correctness and performance issues at all levels of the ML software stack.
- Experience with ML compilers and their internals, experience writing compiler optimization passes.
- Familiarity with accelerator hardware architectures (TPUs/GPUs).
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
On this team, you will own the optimization of the models powering the YouTube algorithm. Your work will focus on model efficiency optimization, such as low-precision quantization , knowledge distillation, parameter sharing, and designing hardware-friendly model architectures, to reduce training and serving costs while maximizing fleet utilization and value delivered to users.
You will build support and optimize new and existing models in our Recommendation System stack, including new model architectures while adapting to next-generation TPU hardware.
You will engage in model and TPU compiler co-design, with opportunities to work across the stack ranging from end-user ML models down to Hardware/Software architecture.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Profile ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
- Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
- Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
- Partner closely with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.
See All 16 Efficiency Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find Efficiency Engineer JobsEfficiency Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Efficiency Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Law & Legal Services
- Electronics & Hardware
What California Employers Look For
The qualifications that appear most often in efficiency engineer jobs across California.
- Bachelor's degree in industrial engineering, mechanical engineering, or a closely related field
- Demonstrated experience applying Lean, Six Sigma, or Kaizen methodologies in a production or operations environment
- Proficiency with process mapping tools and data analysis software such as Minitab or Excel
- Familiarity with California Title 24 energy efficiency standards or equivalent regulatory compliance requirements
- Experience leading cross-functional improvement projects from problem identification through verified results
- Certified Lean Six Sigma Green Belt or Black Belt credential preferred by most California employers
Efficiency Engineer Jobs in California: Frequently Asked Questions
How do you become a efficiency engineer in California?
Most efficiency engineer roles in California require a bachelor's degree in industrial, mechanical, or systems engineering from an accredited program. While California does not require a state license specific to efficiency engineers, many employers prefer candidates who have earned a Lean Six Sigma Green Belt or Black Belt certification. Engineers who want to practice as licensed Professional Engineers may pursue licensure through the California Board for Professional Engineers, Land Surveyors, and Geologists, which adds credibility for senior roles.
How much do efficiency engineers make in California?
Efficiency engineers in California earn a median of about $124,600 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $77,900 for the lowest 10% to over $172,870 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire efficiency engineers in California?
Employers hiring efficiency engineers in California right now include TikTok, Nuro, and Amazon, based on current listings on Migrate Mate as of September 2026. California's concentration of aerospace manufacturers, semiconductor fabs, and large utilities means demand for continuous improvement expertise runs across both traditional heavy industry and high-growth clean energy sectors.
Which California cities have the most efficiency engineer jobs?
San Jose, Sunnyvale, and Mountain View account for the most efficiency engineer openings in California. The distribution reflects where large manufacturing, defense, and technology operations are anchored, with the Bay Area's semiconductor and clean tech campuses, Los Angeles's aerospace and logistics hubs, and San Diego's defense contractors each generating consistent demand for process improvement talent.
Are there remote efficiency engineer jobs in California?
Yes, but they're rare. Efficiency engineering is fundamentally a hands-on discipline tied to physical processes, production floors, and on-site equipment, which limits full remote arrangements. About 38% of efficiency engineer openings tied to California are remote or hybrid as of September 2026, and those positions tend to cover the data analysis, reporting, and project coordination portions of the role rather than active process observation or line-level implementation.
How can I get hired as a efficiency engineer in California with little or no experience?
The most realistic entry path is an industrial or manufacturing engineering internship or co-op arranged through a California university's engineering program, which frequently leads directly to a full-time offer. Large California employers such as Northrop Grumman, Intel, and Pacific Gas and Electric run structured new-graduate rotational programs in operations and continuous improvement. Candidates coming from adjacent roles like quality technician, production coordinator, or facilities analyst can also make a lateral move by pairing that experience with a Lean Six Sigma Yellow or Green Belt certificate to signal readiness for improvement-focused work.
Where can I find and apply to efficiency engineer jobs in California?
You can find and apply to efficiency engineer jobs in California on Migrate Mate, which lists current openings across the state. Search the available roles, find the ones that match your background and preferred location, and apply directly to the ones that fit.
See All 16 Efficiency Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find Efficiency Engineer Jobs