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Scale Jobs in California (NOW HIRING)

Hark

Infrastructure, Large-scale Training

San Jose, CA · On-site

$180K - $450K/yr

About the Role We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll ...

Hark

Infrastructure, Large-scale Training

San Jose, CA · On-site

$180K - $450K/yr

About the Role We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll ...

Braze

Account Executive, Retail Scale

San Francisco, CA · On-site

$74K - $117K/yr

Join a scaling, diverse, and tight-knit team that's working directly with Marketing, Product, and Technical executives and their teams to help them forge human connections between consumers and the ...

Sierra Pacific Industries

Log Scaler

Quincy, CA · On-site

$26.76 - $36.66/hr

Pass scale checks conducted by Sierra Pacific and outside inspection agencies * Be proficient in scaling rules and procedures * Safely and efficiently operate log yard equipment, including front-end ...

Fin

Account Executive, Scale

San Francisco, CA · On-site

$132K - $158K/yr

As a Scale Account Executive, you will be a key member of the team leading the growth of our new business. We're building a world-class sales organization, and the road ahead is going to be very ...

Scale AI

Engagement Manager

San Francisco, CA · On-site

Scale AI is a company focused on developing reliable AI systems for critical decisions. As an Engagement Manager on Scale's Generative AI team, you will manage customer relationships, translate their ...

Braze

Sales Director, Scale Retail

San Francisco, CA · On-site

$120K - $181K/yr

WHAT WE'RE LOOKING FOR This is a SaaS midmarket/scale sales leadership role, managing a team of midmarket/scale Account Executives for Braze's market-leading Customer Journey Orchestration platform.

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Scale information

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How much do scale jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for scale in California is $17.57, according to ZipRecruiter salary data. Most workers in this role earn between $15.19 and $19.47 per hour, depending on experience, location, and employer.

What is the difference between Scale vs Data Analyst?

AspectScaleData Analyst
Required CredentialsTypically requires a degree in business, finance, or related fields; certifications like CFA or CPA are commonUsually requires a degree in statistics, mathematics, or computer science; certifications like CAP or Microsoft Data Analyst are beneficial
Work EnvironmentOften in corporate or financial settings, focusing on large-scale business operationsPrimarily in offices, working with data sets, spreadsheets, and analytics tools
Employer & Industry UsageUsed by financial institutions, consulting firms, and large corporations for strategic planningUsed across industries including finance, marketing, healthcare, and tech for data-driven decision making

While both roles involve analysis, Scale focuses on large-scale business or financial operations, whereas Data Analysts concentrate on interpreting data to inform decisions. Understanding these differences helps in choosing the right career path or job search focus.

What is a scale?

Scale jobs typically refer to roles involved in scaling a business, project, or system to handle increased growth, demand, or complexity. These positions often focus on optimizing processes, expanding infrastructure, and ensuring that operations can efficiently support larger volumes. Common scale roles exist in technology (like scaling software systems), operations, and startups aiming for rapid growth. Professionals in these jobs are skilled at problem-solving, automation, and strategic planning to ensure seamless expansion.

What are the key skills and qualifications needed to thrive as a scale operator?

To thrive as a Scale Operator, you need attention to detail, basic math skills, and familiarity with weight measurement, often supported by a high school diploma or equivalent. Proficiency in operating digital and manual scales, as well as using inventory and logistics management software, is typically required. Strong organizational skills, accuracy, and effective communication make someone stand out in this position. These skills ensure precise measurements, regulatory compliance, and smooth workflow in shipping, manufacturing, or logistics environments.

What are the most common challenges faced by professionals working in scale-up operations, and how can they be addressed?

Professionals in scale-up operations often encounter challenges such as managing rapid growth, optimizing processes for increased volume, and maintaining quality while scaling. Balancing the need for agility with the implementation of more structured workflows is also a common hurdle. Successful scale-up teams address these challenges by prioritizing clear communication, leveraging data-driven decision-making, and fostering a culture of continuous improvement. Collaboration across departments—such as engineering, production, and quality assurance—is essential to ensure smooth transitions and sustained growth.
What are popular job titles related to Scale jobs in California? For Scale jobs in California, the most frequently searched job titles are:
What job categories do people searching Scale jobs in California look for? The top searched job categories for Scale jobs in California are:
What cities in California are hiring for Scale jobs? Cities in California with the most Scale job openings:
Scale jobs near you
Infographic showing various Scale job openings in California as of August 2026, with employment types broken down into 79% Full Time, 15% Part Time, 2% Temporary, and 4% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $36,547 per year, or $17.6 per hour.

Infrastructure, Large-scale Training

Hark

San Jose, CA • On-site

$180K - $450K/yr

Full-time

Re-posted 21 days ago

Job description

About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
About the Role
We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll work at the intersection of systems engineering and machine learning infrastructure, owning the reliability, scalability, and efficiency of the compute platform that our research and engineering teams depend on. This is a high-impact, highly technical role suited for someone who thrives in complex distributed systems environments and cares deeply about infrastructure as a product.
Responsibilities
  • Design, implement, and maintain Infrastructure as Code (IaC) best practices to enable repeatable, auditable, and scalable cluster provisioning.
  • Enhance and harden CI/CD deployment pipelines to ensure robust, secure, and low-latency model service delivery across production environments.
  • Own and evolve stable training infrastructure operating at the scale of 10,000+ GPUs, including job scheduling, fault tolerance, and network fabric optimization.
  • Partner closely with ML researchers and engineers to understand compute bottlenecks and translate them into infrastructure improvements.
  • Monitor system health, define SLOs, and lead incident response for critical training and inference workloads.
  • Drive capacity planning, cost efficiency initiatives, and hardware lifecycle management across the GPU fleet.
  • Contribute to internal tooling and platform abstractions that improve developer experience for teams consuming compute resources.

Requirements
  • 5+ years of experience in infrastructure, systems, or platform engineering, with at least 2 years working in ML or HPC environments.
  • Demonstrated experience managing GPU clusters or large-scale distributed compute infrastructure.
  • Strong proficiency in at least one systems or infrastructure programming language.
  • Deep understanding of networking fundamentals (RDMA, InfiniBand, or RoCE a plus) relevant to high-throughput training workloads.
  • Experience with container orchestration, job scheduling, and multi-tenant resource management.
  • Proven track record owning production systems with high reliability requirements.
  • Strong debugging and observability skills across the full infrastructure stack.

Bonus Qualifications
  • Kubernetes (K8s) - particularly experience operating large, GPU-aware clusters.
  • Pulumi or similar modern IaC tooling.
  • Rust and/or Go for systems-level tooling and performance-critical services.
  • Familiarity with PyTorch and Ray for understanding workload patterns and integration requirements.

Compensation
The US base salary range for this full-time position is between $180,000 - $450,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components and benefits depending on the specific role. This information will be shared if an employment offer is extended.

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