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Benchmarking Jobs in California (NOW HIRING)

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Benchmarking information

See California salary details

$50.3K

$79.3K

$112.5K

How much do benchmarking jobs pay per year?

As of Jun 30, 2026, the average yearly pay for benchmarking in California is $79,334.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,100.00 and $85,900.00 per year, depending on experience, location, and employer.

What is an example of a benchmark job?

A benchmark job is a standard position used for comparing compensation, skills, or performance across organizations. For example, a registered nurse or software engineer role often serves as a benchmark because they are common, well-defined, and have established salary ranges and job descriptions. These roles help organizations set pay scales and evaluate employee performance based on industry standards.

How does a Benchmarking Analyst typically collaborate with other departments to drive performance improvements?

Benchmarking Analysts frequently work cross-functionally, partnering with teams such as operations, finance, and quality assurance to collect data and compare organizational performance against industry standards. They facilitate workshops, share insights, and help identify actionable areas for improvement. This collaborative approach ensures that recommendations are tailored to each department's unique challenges and that initiatives are widely supported and successfully implemented.

What are the key skills and qualifications needed to thrive as a Benchmarking Analyst, and why are they important?

To thrive as a Benchmarking Analyst, you need strong analytical skills, attention to detail, and a background in business, statistics, or related fields. Familiarity with data analysis tools like Excel, SQL, or benchmarking software, as well as certifications such as Six Sigma, are often valuable. Excellent communication, critical thinking, and problem-solving abilities help you interpret data and present actionable insights to stakeholders. These skills are crucial for driving performance improvements and maintaining competitiveness by accurately comparing organizational practices against industry standards.

What jobs pay 2000 a day?

High-level consulting, executive coaching, and specialized freelance roles such as management consultants, financial advisors, or legal experts can earn around $2,000 per day. These positions typically require extensive experience, advanced skills, and often involve project-based or client-specific work. Compensation varies based on industry, location, and individual expertise.

What is the difference between Benchmarking vs Data Analyst?

AspectBenchmarkingData Analyst
Required credentialsOften requires business or industry-specific certifications, degrees in business, economics, or related fieldsTypically requires degrees in statistics, mathematics, or computer science; certifications like CAP or Microsoft Data Analyst
Work environmentPrimarily in corporate, manufacturing, or consulting settings focusing on performance comparisonIn various industries, working with data sets, reporting, and data visualization tools
Employer and industry usageUsed by organizations to improve processes by comparing against best practicesUsed across industries for data analysis, reporting, and decision-making support

While Benchmarking focuses on comparing organizational performance to industry standards, Data Analysts interpret data to inform business decisions. Both roles require analytical skills but serve different strategic purposes within organizations.

What is a benchmark job?

A benchmark job is a standard or reference position used by organizations to compare compensation, skills, and job requirements across similar roles. It helps in establishing pay scales and evaluating job market competitiveness, often requiring knowledge of industry standards and job analysis tools.

What is the best example of a benchmarked job?

A benchmarked job is one that has been compared against industry standards or best practices to determine appropriate compensation, skills, or performance levels. Examples include roles like software engineer or project manager, where salary ranges and responsibilities are often standardized through salary surveys and market analysis. Benchmarking helps organizations ensure competitive pay and effective role definitions.

What is benchmarking?

Benchmarking is the process of comparing a company's products, services, or processes against those of leading organizations in the industry or best practices from other industries. The goal is to identify areas where improvements can be made to increase efficiency, quality, or competitiveness. Benchmarking often involves collecting data, analyzing performance metrics, and implementing changes based on findings. This strategic approach helps organizations stay competitive and continuously improve their operations.
What are popular job titles related to Benchmarking jobs in California? For Benchmarking jobs in California, the most frequently searched job titles are:
What job categories do people searching Benchmarking jobs in California look for? The top searched job categories for Benchmarking jobs in California are:
What cities in California are hiring for Benchmarking jobs? Cities in California with the most Benchmarking job openings:
Benchmarking jobs near you

Research Engineer - Benchmarking, Evals & Failure Analysis

Mercor

San Francisco, CA • On-site

$130K - $500K/yr

Full-time

Medical, Dental, Vision

Posted 14 days ago

Job description

About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $3 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You'll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
As a Research Engineer at Mercor, you'll work at the intersection of engineering and applied AI research. You'll own benchmarking pipelines, evaluation systems, and failure analysis workflows that directly inform how we train and improve frontier language models.
Your work will define how we measure tool use, agentic behavior, and real-world reasoning. You'll design and run evals, build rubrics and scorers, and turn failure analysis into actionable improvements for post-training, RLVR, and data pipelines.
What You'll Do
  • Benchmarking: Design, implement, and maintain benchmarks and metrics for tool use, agentic behavior, and real-world reasoning; ensure benchmarks scale with training and stay aligned with product and research goals.
  • Evaluation systems: Build and operate LLM evaluation systems end-to-end runs, scoring, dashboards, and reporting, so researchers and applied AI teams can track model performance and compare runs at scale.
  • Failure analysis: Run systematic failure analysis on model outputs (e.g., wrong tool use, reasoning errors, safety/alignment issues); categorize failure modes, quantify prevalence, and feed findings into reward design, data curation, and benchmark design.
  • Rubrics and evaluators: Create and refine rubrics, automated evaluators, and scoring frameworks that drive training and evaluation decisions; balance rigor with scalability (human vs. model-as-judge, calibration, agreement).
  • Data quality and usability: Quantify data usability, quality, and impact on key benchmarks; use evals and failure analysis to guide data generation, augmentation, and curation.
  • Cross-team collaboration: Work with AI researchers, applied AI teams, and data producers to align evals with training objectives and to prioritize benchmarks and failure analyses that matter most.
  • Ownership in a fast-paced environment: Operate in a high-iteration research setting with strong ownership of benchmarks, evals, and failure-analysis workflows.
What We're Looking For
  • Strong applied research background, with focus on model evaluation, benchmarking, and/or failure analysis.
  • Strong coding skills and hands-on experience with ML models and evaluation code.
  • Solid grasp of data structures, algorithms, and backend systems.
  • Comfort with APIs, SQL/NoSQL, and cloud platforms for running and storing eval results.
  • Ability to reason about model behavior, experimental results, and data quality from evals and failure analyses.
  • Excitement to work in person in San Francisco five days a week in a high-intensity, high-ownership environment.
Nice To Have
  • Industry experience on a post-training or evaluation/benchmarking team (highest priority).
  • Publications at top-tier venues (NeurIPS, ICML, ACL), especially in evaluation or benchmarking.
  • Experience building or running LLM evaluations, benchmarks, or failure-analysis pipelines.
  • Experience with synthetic data generation, rubric design, or RL-style workflows that use evals for reward shaping.
  • Work samples or code (e.g., eval frameworks, benchmark suites, failure-analysis reports or tooling) that demonstrate relevant skills.
Benefits
  • Bi-annual performance bonus structure
  • Generous equity grant vested over 4 years
  • Up to $15k Relocation bonus
  • $10K housing bonus (if you live within 0.5 miles of our office)
  • $1.5K monthly stipend for meals
  • Free Equinox membership
  • $200 monthly laundry reimbursement
  • $200 monthly personal wellness reimbursement
  • Health, Dental, Vision insurance

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