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Optimization Engineer Jobs in California (NOW HIRING)

Hitachi

Senior Optimization Engineer

Santa Clara, CA · Remote

$122K - $168K/yr

As a Senior Optimization Engineer, you will work at the intersection of advanced mathematics, software engineering, and power systems. You'll design and implement optimization models that help ...

Hitachi, Ltd.

Senior Optimization Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

As a Senior Optimization Engineer, you will work at the intersection of advanced mathematics, software engineering, and power systems. You'll design and implement optimization models that help ...

Etched

Power Optimization Engineer

Cupertino, CA

$2.0K/mo

Work closely with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to implement design for optimal power using advanced power management ...

Etched

Power Optimization Engineer

Cupertino, CA · On-site

$2.0K/mo

Work closely with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to implement design for optimal power using advanced power management ...

Apple

Sr. ML Optimization Engineer, iCloud

Cupertino, CA · On-site

$128K - $177K/yr

As a Sr. ML Optimization Engineer, you will work at the intersection of systems engineering, infrastructure strategy, applied analytics, machine learning, and large-scale optimization. You will have ...

Etched

Power Optimization Engineer

Cupertino, CA

$2.0K/mo

Work closely with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to implement design for optimal power using advanced power management ...

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Optimization Engineer information

See California salary details

$40

$58

$80

How much do optimization engineer jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for optimization engineer in California is $58.87, according to ZipRecruiter salary data. Most workers in this role earn between $42.69 and $72.60 per hour, depending on experience, location, and employer.

What jobs will boom in 2026?

Optimization engineers are expected to see increased demand as companies focus on improving efficiency through data analysis, automation, and machine learning. Skills in programming, statistical modeling, and familiarity with tools like Python or MATLAB will be valuable, and roles may involve working in technology, manufacturing, or logistics sectors.

What is the difference between Optimization Engineer vs Data Analyst?

AspectOptimization EngineerData Analyst
Required CredentialsBachelor's in Engineering, Mathematics, or related field; often certifications in optimization or data analysisBachelor's in Statistics, Mathematics, or related field; certifications in data analysis tools
Work EnvironmentEngineering teams, manufacturing, logistics, or software developmentBusiness, finance, marketing, or healthcare sectors
Employer & Industry UsageManufacturing, tech, logistics, supply chainFinance, marketing, healthcare, consulting

Optimization Engineers focus on improving processes and systems through mathematical modeling and algorithms, often working in technical environments. Data Analysts interpret data to support business decisions, typically working with data visualization and reporting tools. While both roles analyze data, Optimization Engineers emphasize process optimization, whereas Data Analysts focus on insights and reporting.

What are Optimization Engineers?

Optimization Engineers are professionals who analyze, design, and implement solutions to improve the efficiency, performance, and cost-effectiveness of systems, processes, or products. They use mathematical models, data analysis, and simulation tools to identify areas for improvement and develop strategies to achieve optimal results. These engineers work across various industries, including manufacturing, technology, energy, and logistics, to help organizations maximize output while minimizing resources and waste.

What are the key skills and qualifications needed to thrive as an Optimization Engineer, and why are they important?

To thrive as an Optimization Engineer, you need a solid background in mathematics, data analysis, and engineering principles, often supported by a degree in engineering, mathematics, or a related field. Familiarity with optimization software (such as Gurobi, CPLEX, or MATLAB), programming languages like Python, and data modeling tools is typically required. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in this role. These skills and qualities are crucial for developing efficient solutions, collaborating with cross-functional teams, and driving continuous improvement in complex systems.

What does an optimization engineer do?

An optimization engineer analyzes and improves processes, systems, or algorithms to increase efficiency, reduce costs, or enhance performance. They often use mathematical modeling, data analysis, and tools like MATLAB or Python to develop solutions and may work in industries such as manufacturing, logistics, or software development.

How does an Optimization Engineer typically collaborate with other departments to implement solutions?

Optimization Engineers often work closely with cross-functional teams such as production, operations, and data analysis. They collaborate by gathering input on current processes, identifying bottlenecks, and proposing data-driven improvements. Regular meetings and clear communication are crucial to ensure that proposed optimizations are practical and align with business goals. By involving stakeholders from various departments, Optimization Engineers help facilitate smoother implementation and ensure that solutions are sustainable and well-integrated.

What engineers make $500,000?

Senior engineers in fields such as software, petroleum, and aerospace engineering can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. High compensation often includes bonuses, stock options, or profit sharing, particularly in large companies or high-demand industries.

What Is Optimization Engineering?

The job duties of an optimization engineer focus on taking an existing design and improving making it stronger, fast, more efficient, or more durable. Career qualifications for an optimization engineer include a bachelor’s or master’s degree in engineering and years of field experience through internships or similar positions. Strong analytical and research skills are important for this job, as well as a strong background in advanced mathematics.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, and systems engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Roles often require strong technical expertise, certifications, and leadership responsibilities.
More about Optimization Engineer jobs
What are the most commonly searched types of Optimization Engineer jobs in California? The most popular types of Optimization Engineer jobs in California are:
What are popular job titles related to Optimization Engineer jobs in California? For Optimization Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Optimization Engineer jobs in California look for? The top searched job categories for Optimization Engineer jobs in California are:
What are popular job titles related to Optimization Engineer jobs in CA? For Optimization Engineer jobs in CA, the most frequently searched job titles are:
Optimization Engineer jobs near you
Infographic showing various Optimization Engineer job openings in California as of June 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $122,442 per year, or $58.9 per hour.

Compiler Optimization Engineer

Lemurian Labs

Santa Clara, CA

Other

Medical, Dental, Vision, Retirement

Posted 18 days ago

Job description

About the Role

We're looking for a Graph Optimization Compiler Engineer to own the middle tier of our AI compiler stack - the layer where high-level model graphs are transformed, simplified, and made ready for efficient code generation. You'll design and implement the optimization passes that make the difference between a model that runs and a model that flies.

This role sits between our compiler front end and code generation backend. You'll work on graph-level transformations - fusion, layout optimization, dead code elimination, constant folding, and more - with a direct line of sight to the performance outcomes your work produces. If you think in data flow graphs and optimization passes, and you want that thinking to power the next generation of AI infrastructure, we'd love to talk.

What You'll Do
  • Design, develop, and maintain the graph optimization layer of our heterogeneous AI compiler
  • Implement and extend graph-level transformation passes including operator fusion, layout propagation, dead code elimination, constant folding, and algebraic simplification
  • Define and evolve our intermediate representation (IR) to support new optimization opportunities as ML model architectures advance
  • Analyze performance data to identify optimization gaps and drive measurable improvements in throughput and latency
  • Collaborate with front end and code generation teams to ensure clean IR interfaces and well-structured optimization pipelines
  • Propose and prototype new optimization strategies in response to advances in model design and hardware capabilities
  • Contribute to testing and validation infrastructure to ensure optimization correctness across model types and hardware targets
RequirementsEssential Skills and Experience
  • BS degree in Computer Science, Computer Engineering, or equivalent practical experience
  • 4+ years of experience working with compilers, with a focus on intermediate representation design or optimization passes
  • Deep knowledge of graph-level compiler optimization techniques - fusion, tiling, layout transformations, and related methods
  • 4+ years of experience with C/C++
  • Strong written and verbal communication skills; ability to write clear and concise technical documentation
Preferred Skills and Experience
  • Master's or PhD in Computer Science, Computer Engineering, or equivalent
  • Experience with polyhedral models or affine analysis for loop and tensor optimization
  • Familiarity with hardware memory hierarchies and how layout decisions impact performance on GPUs or accelerators
  • Experience working with MLIR, XLA, or similar graph-level IR frameworks
  • Experience with ML framework internals - PyTorch eager/compile mode, JAX/XLA, or TensorRT
  • Strong understanding of ML model architectures and their computational patterns (attention, convolution, normalization, etc.)
  • Knowledge of quantization, sparsity, or other model-level optimization techniques
  • Contributions to open-source compiler or ML infrastructure projects
Why Join Lemurian Labs
  • Own a critical layer of our compiler stack where optimization decisions have direct, measurable impact on model performance
  • Work on the hardest graph-level problems in AI infrastructure - across diverse hardware targets and model architectures
  • Collaborate with a team that treats infrastructure as a canvas and optimization as a craft
  • Competitive compensation including equity, medical/dental/vision, retirement savings, and wellness benefits


Apply