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$32.1K

$67.4K

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How much do high performance jobs pay per year?

As of Jun 7, 2026, the average yearly pay for high performance in California is $67,355.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,300.00 and $81,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a High Performance Coach, and why are they important?

To thrive as a High Performance Coach, you need a deep understanding of performance psychology, goal setting, and behavior change, typically supported by a background in coaching, sports science, or psychology. Familiarity with assessment tools, data analytics platforms, and relevant certifications such as ICF or NLP are commonly required. Outstanding interpersonal skills, motivational ability, and adaptability help coaches build trust and effectively support clients through challenges. These skills ensure clients achieve sustained growth, maximize their potential, and maintain high levels of motivation and productivity.

What is the difference between High Performance vs Data Analyst?

AspectHigh PerformanceData Analyst
Required CredentialsRelevant certifications, technical skills, performance metricsDegree in statistics, mathematics, or related field; data analysis certifications
Work EnvironmentFast-paced, results-driven teams, often in tech or financeOffice setting, data-focused projects across industries
Employer & Industry UsageTech companies, finance, consulting firms emphasizing high productivityBusinesses needing data insights across sectors
Search & Comparison IntentUnderstanding high-performing roles, performance standardsAnalyzing data roles, skills, and career paths

High Performance roles focus on exceeding productivity and efficiency metrics within fast-paced environments, often requiring specialized skills and certifications. Data Analysts interpret data to inform business decisions, typically with a focus on data collection, analysis, and reporting. While both roles demand analytical skills, High Performance emphasizes output and results, whereas Data Analysts concentrate on data insights and interpretation.

What are some common challenges faced by professionals in high performance roles, and how can they be managed?

Professionals in high performance roles often encounter challenges such as managing high expectations, maintaining consistent results under pressure, and balancing workload with personal well-being. To address these, it's important to develop strong time management skills, seek feedback regularly, and leverage teamwork to distribute responsibilities effectively. Many organizations also provide resources such as coaching or mental health support to help team members sustain peak performance while avoiding burnout.

What are High Performance jobs?

High Performance jobs typically refer to roles focused on maximizing the efficiency, productivity, and outcomes of individuals or teams, often within sports, business, or technology sectors. These positions may include High Performance Managers, Coaches, or Directors who develop and implement strategies to achieve top results. Responsibilities often involve analyzing performance data, setting goals, and providing support to reach peak performance. High Performance jobs require strong leadership, analytical skills, and a deep understanding of the relevant field. They are crucial in environments where excellence and continuous improvement are priorities.
What are popular job titles related to High Performance jobs in California? For High Performance jobs in California, the most frequently searched job titles are:
What job categories do people searching High Performance jobs in California look for? The top searched job categories for High Performance jobs in California are:
High Performance jobs near you
Infographic showing various High Performance job openings in California as of May 2026, with employment types broken down into 1% As Needed, 90% Full Time, 7% Part Time, 1% Temporary, and 1% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $67,355 per year, or $32.4 per hour.

High Performance Computing (HPC) Engineer

GenBio AI

Palo Alto, CA • On-site

Full-time

Posted yesterday

Job description

Job Summary:
GenBio AI is a newly established start-up headquartered in Silicon Valley, dedicated to transforming biology and medicine through Generative AI. The HPC Engineer will design, deploy, and maintain high-performance GPU clusters, implement distributed computing techniques, and collaborate with data scientists to enhance model development and deployment frameworks.
Responsibilities:
• GPU Cluster Management: Design, deploy, and maintain high-performance GPU clusters, ensuring their stability, reliability, and scalability. Monitor and manage cluster resources to maximize utilization and efficiency.
• Distributed/Parallel Training: Implement distributed computing techniques to enable parallel training of large deep learning models across multiple GPUs and nodes. Optimize data distribution and synchronization to achieve faster convergence and reduced training times.
• Performance Optimization: Fine-tune GPU clusters and deep learning frameworks to achieve optimal performance for specific workloads. Identify and resolve performance bottlenecks through profiling and system analysis.
• Deep Learning Framework Integration: Collaborate with data scientists and machine learning engineers to integrate distributed training capabilities into GenBio AI’s model development and deployment frameworks.
• Scalability and Resource Management: Ensure that the GPU clusters can scale effectively to handle increasing computational demands. Develop resource management strategies to prioritize and allocate computing resources based on project requirements.
• Troubleshooting and Support: Troubleshoot and resolve issues related to GPU clusters, distributed training, and performance anomalies. Provide technical support to users and resolve technical challenges efficiently.
• Documentation: Create and maintain documentation related to GPU cluster configuration, distributed training workflows, and best practices to ensure knowledge sharing and seamless onboarding of new team members.
Qualifications:
Required:
• Master’s or Ph.D. degree in computer science, or a related field with a focus on High-Performance Computing, Distributed Systems, or Deep Learning.
• 2+ years proven experience in managing GPU clusters, including installation, configuration, and optimization.
• Strong expertise in distributed deep learning and parallel training techniques.
• Proficiency in popular deep learning frameworks like PyTorch, Megatron-LM, DeepSpeed, etc.
• Programming skills in Python and experience with GPU-accelerated libraries (e.g., CUDA, cuDNN).
• Knowledge of performance profiling and optimization tools for HPC and deep learning.
• Familiarity with resource management and scheduling systems (e.g., SLURM, Kubernetes)
• Strong background in distributed systems, cloud computing (AWS, GCP), and containerization (Docker, Kubernetes)
Company:
GenBio AI creates AI-driven models to simulate and predict biological systems at multiple scales. Founded in 2024, the company is headquartered in Palo Alto, USA, with a team of 11-50 employees. The company is currently Early Stage.

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