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Linear Jobs in California (NOW HIRING)

Sptix

Frontend Engineer

San Francisco, CA · On-site

$120 - $180/hr

Frontend Engineer Sign in for personalized insights, salary data & more Help build the Linear app -- the issue tracker high-performance teams swear by. You will own pixel-perfect, performance ...

HiredFirst

Radiation Therapist (Outpatient)

Lodi, CA · On-site

$80 - $85/hr

Position Overview The Radiation Therapist will administer prescribed radiation treatments to oncology patients using advanced linear accelerator equipment. This role requires precision, strong ...

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How much do linear jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for linear in California is $37.17, according to ZipRecruiter salary data. Most workers in this role earn between $33.46 and $39.62 per hour, depending on experience, location, and employer.

What is a linear engineer?

Linear engineers are professionals who specialize in the design, analysis, and implementation of linear systems, which are systems whose output is directly proportional to their input. This often involves working with linear equations, signal processing, and control systems in fields like electrical engineering, communications, and automation. Linear engineers use mathematical models and software tools to optimize system performance, troubleshoot issues, and ensure reliable operation. Their work is crucial in industries ranging from telecommunications to robotics.

How does a linear product manager typically collaborate with engineering and design teams to deliver new features?

As a Linear Product Manager, you play a central role in ensuring seamless collaboration between engineering and design teams. You are responsible for clearly communicating product goals, prioritizing feature requests, and facilitating regular meetings such as sprint planning and retrospectives. This involves balancing technical feasibility with user experience considerations and aligning all stakeholders on timelines and deliverables. Open communication, documentation, and use of project management tools like Linear are essential for tracking progress and resolving blockers efficiently.

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

To excel as a Linear Programmer, you need a strong background in mathematics, operations research, and optimization techniques, typically supported by a relevant degree in mathematics, engineering, or computer science. Familiarity with technical tools such as MATLAB, Python with optimization libraries, and specialized linear programming solvers like CPLEX or Gurobi is common. Analytical thinking, problem-solving skills, and attention to detail are crucial soft skills that help address complex optimization challenges. These competencies are important because they enable the creation of efficient solutions for resource allocation, logistics, and decision-making in various industries.

What is the difference between Linear vs Software Developer?

AspectLinearSoftware Developer
Required CredentialsTypically a technical degree or relevant certificationsUsually a computer science or related degree, certifications vary
Work EnvironmentTech companies, startups, project management toolsSoftware companies, tech departments, freelance projects
Industry UsageProject management, product developmentApplication development, coding, system design
Common Search/ComparisonOften compared for workflow tools and project managementCompared for coding skills and software creation

Linear is a project management tool used mainly in tech and startup environments, focusing on issue tracking and workflow. Software Developers create and maintain software applications, requiring coding skills and technical knowledge. While both roles are tech-related, Linear is a tool or platform, whereas Software Developer is a profession involving programming and software design.

What is a linear career?

A linear career refers to a professional path where an individual progresses steadily within a specific field or role, often through promotions or increased responsibilities. This type of career typically involves gaining experience, skills, and expertise over time, with clear advancement steps. It is common in professions that value specialization and continuous growth within a particular area.

What is linear work?

Linear work typically refers to jobs that involve tasks performed in a straight, sequential manner, often requiring consistent routines or processes. These roles may involve repetitive tasks, use of specific tools or machinery, and often follow a set schedule or workflow. Examples include assembly line work, data entry, or manufacturing roles.

What are popular job titles related to Linear jobs in California?

For Linear jobs in California, the most frequently searched job titles are:

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

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

What cities in California are hiring for Linear jobs?

Cities in California with the most Linear job openings:

Linear jobs near you
Infographic showing various Linear job openings in California as of August 2026, with employment types broken down into 96% Full Time, and 4% Temporary. Highlights an 96% In-person, and 4% Hybrid job distribution, with an average salary of $77,304 per year, or $37.2 per hour.

Member of Technical Staff - Extreme-Scale Sparse Linear Algebra, Domain Decomposition & GPU Solver A

Vinci AI

Palo Alto, CA • On-site

$100K - $220K/yr

Full-time

Re-posted 14 days ago

Job description

Member of Technical Staff - Extreme-Scale Sparse Linear Algebra, Domain Decomposition & GPU Solver Architecture
Vinci | Full-Time | Remote / Hybrid
The Mission
At Vinci, we are building the AI-enabled infrastructure that modern hardware programs use to converge on physics decisions with confidence.
Our software delivers manufacturing-resolution physics simulation with verified accuracy at orders-of-magnitude faster runtimes than traditional tools, bypassing meshing and approximation overhead entirely.
We are deployed or in active validation with a broad range of Tier-1 ecosystem players - across semiconductor IDMs, foundries, advanced packaging, fabless companies, automotive, EMS, and energy hardware development. This means real solver constraints, not benchmarks. Simulation decisions here drive actual hardware outcomes, with diverse operator structures and conditioning regimes.
Now we are building the core solver substrate that must scale beyond billions of DOFs - to trillions, preserve determinism, and generalize across radically different operator landscapes and distributed environments.
The Challenge
This role is about the core numerical substrate, not application wrappers:
  • Conditioning and convergence at extreme scale
  • Domain decomposition and Schwarz theory at production scale
  • Robust, multilevel and multigrid, preconditioning
  • Communication-avoiding Krylov and hierarchical solvers
  • Deterministic parallel reductions across GPU clusters
  • AI-accelerated solver components grounded in numerical rigor

Your work will shape the solver architecture that supports not just a single physics, but a rich operator ecosystem including indefinites, saddle-point systems, strong coefficient jumps, anisotropy, and tightly coupled multiphysics blocks encountered in real hardware workflows.
What You Will Build
You will own the design and delivery of production-grade solver infrastructure, including:
Domain Decomposition & Schwarz Methods
  • Additive and multiplicative Schwarz frameworks
  • Overlapping and non-overlapping strategies
  • Scalable coarse space construction
  • Hybrid coarse/fine hierarchies for production meshes

Preconditioning at Extreme Scale
  • Algebraic and geometric multigrid
  • Block/physics-aware preconditioners
  • ILU variants, sparse approximate inverses
  • Communication-efficient preconditioner designs

Krylov & Solver Architecture
  • CG, GMRES/FGMRES, BiCGStab
  • Pipelined/communication-reducing methods
  • Mixed-precision strategies with robustness guarantees
  • Deterministic reduction ordering over distributed execution

AI-Augmented Solver Enhancements
  • Learned augmentations for coarse space discovery
  • Adaptive preconditioner selection
  • Spectral approximations and operator compression

AI here supports numerical structure, not replaces it.
What We're Looking For
You bring deep expertise in:
  • Domain decomposition and Schwarz methods
  • Multilevel solvers and scalable preconditioning
  • Large sparse systems at extreme scale
  • Parallel numerical stability and conditioning
  • GPU-accelerated sparse linear algebra (CUDA + HIP)
  • Multi-GPU and distributed execution paradigms

You think about:
  • Spectral equivalence and coarse space quality
  • Strong/weak scaling tradeoffs
  • Communication vs computation balance

You've shipped real solver infrastructure - not just prototypes.
Systems & Engineering Expectations
  • CUDA first, HIP appreciated
  • Kernel-level performance engineering
  • Multi-GPU scaling experience
  • Strong CI, regression, and correctness validation disciplines

You understand how algorithms map to hardware and survive production pressure.
Shipping Focus
This is an execution-oriented principal engineering role in a startup with real production deployment. You will:
  • Architect foundational solver systems
  • Implement and ship into Tier-1 environments
  • Build continuous validation and regression frameworks
  • Improve throughput and determinism under real constraints

We are ambitious - but we ship solutions that matter.
Why Vinci
  • Already proven at scale with real validation across Tier-1 ecosystem participants.
  • Physics-first software built on verified methods, not heuristics.
  • A small, technically serious team with deep domain expertise.
  • High ownership, equity participation
  • Production impact - not academic benchmarks

If you think:
  • Trillion-DOF problems are architectural - not just hardware -
  • Deterministic, robust solver substrates are the heart of future physics infrastructure
  • AI should augment numerical authority, not override it

This role was designed for you.
Bottom Line
We are building the solver core that enables deterministic physics infrastructure - validated inside real hardware workflows and ready to scale beyond today's limits.

Apply