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Optimization Jobs in California (NOW HIRING)

Firm Media Inc

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Search Engine Optimization (SEO) Specialist

Ontario, CA · On-site

$25 - $29/hr

Your expertise in SEO techniques and best practices will be essential in achieving client goals. RESPONSIBILITIES: Strategy Alignment and Implementation: * Adhere to the overarching strategy set ...

Diageo

Analyst Space Optimization

Aliso Viejo, CA · On-site

: Analyst Space Optimization Location: Southern CA About Diageo With over 200 brands sold in nearly 180 countries, Diageo is home to some of the world's most iconic drinks. From Johnnie Walker and ...

DIAGEO PLC

Analyst Space Optimization

Aliso Viejo, CA · On-site +1

: Analyst Space Optimization Location: Southern CA About Diageo With over 200 brands sold in nearly 180 countries, Diageo is home to some of the world's most iconic drinks. From Johnnie Walker and ...

UCI group

Business Optimization Specialist

Irvine, CA · On-site

$90 - $120/hr

Responsibilities The Business Process Optimization Analyst supports DFA's efforts to improve operational efficiency and service delivery across administrative functions. This role analyzes existing ...

Living Spaces - Corporate

SEO Analyst

La Mirada, CA · On-site

$81K - $108K/yr

Position Summary The SEO Analyst will be primarily focused on reporting, analytics, and technical audits to drive data-driven SEO strategies for livingspaces.com. This role will collaborate closely ...

Living Spaces

SEO Analyst

La Mirada, CA · On-site

$81K - $108K/yr

Position Summary The SEO Analyst will be primarily focused on reporting, analytics, and technical audits to drive data-driven SEO strategies for livingspaces.com. This role will collaborate closely ...

Living Spaces

Be Seen First

SEO Analyst

La Mirada, CA · On-site

$81K - $108K/yr

The SEO Analyst will be primarily focused on reporting, analytics, and technical audits to drive data-driven SEO strategies for livingspaces.com. This role will collaborate closely with the in-house ...

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All JobsOptimization JobsOptimization Jobs in California

Optimization information

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$40

$58

$80

How much do optimization jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for optimization 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 is an optimization job?

Optimization jobs refer to roles that focus on improving systems, processes, or products to achieve the best possible performance, efficiency, or outcomes. These positions can be found in various industries, including engineering, data science, logistics, and business operations. Professionals in optimization analyze data, identify inefficiencies, and develop solutions using mathematical models, algorithms, or process improvements. Their goal is to maximize value while minimizing costs or resource use. Common job titles in this field include Optimization Engineer, Data Optimization Analyst, and Operations Research Analyst.

What are some common challenges faced by professionals in optimization roles, and how can they be addressed?

Professionals in optimization roles often encounter challenges such as dealing with incomplete or noisy data, balancing multiple and sometimes conflicting objectives, and ensuring that solutions are scalable for real-world implementation. Addressing these challenges requires strong analytical skills, collaboration with domain experts, and the ability to communicate complex concepts to non-technical stakeholders. Leveraging advanced tools and staying updated with the latest optimization techniques can also enhance problem-solving capabilities and contribute to project success.

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

To thrive as an Optimization Specialist, you need strong analytical skills, a background in mathematics or engineering, and experience with data-driven decision-making. Familiarity with optimization software (such as Gurobi or CPLEX), programming languages like Python or R, and relevant certifications in operations research or analytics are typically required. Attention to detail, problem-solving abilities, and effective communication are essential soft skills for interpreting results and collaborating with stakeholders. These skills and qualities are crucial for identifying optimal solutions, improving efficiency, and delivering measurable business value.

What is the difference between Optimization vs Data Analyst?

AspectOptimizationData Analyst
Required CredentialsOften requires degrees in mathematics, statistics, or related fields; certifications like Google Data Studio or Six SigmaTypically requires degrees in statistics, computer science, or related fields; certifications like Microsoft Excel or Tableau
Work EnvironmentPrimarily analytical, project-based, often in marketing, e-commerce, or manufacturingData-driven, reporting-focused, in various industries including finance, healthcare, and tech
Employer & Industry UsageUsed by companies aiming to improve processes, efficiency, and performanceUsed by organizations to interpret data, generate reports, and support decision-making

While both roles involve data analysis, Optimization focuses on improving processes and performance through analytical techniques, whereas Data Analysts primarily interpret data and generate reports to inform business decisions.

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

The most popular types of Optimization jobs in California are:

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

The top searched job categories for Optimization jobs in California are:

What cities in California are hiring for Optimization jobs?

Cities in California with the most Optimization job openings:

Optimization jobs near you
Infographic showing various Optimization job openings in California as of August 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% 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 • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
Lemurian Labs is reimagining the foundations of computing to make AI accessible to everyone. The Compiler Optimization Engineer will own the middle tier of the AI compiler stack, focusing on graph-level transformations and optimization passes to enhance model performance.
Responsibilities:
• 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
Qualifications:
Required:
• 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:
• 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
Company:
Any workload. Any hardware. Any scale. Founded in 2018, the company is headquartered in Santa Clara, USA, with a team of 11-50 employees. The company is currently Early Stage.

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