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Full Time Linear Algebra Jobs (NOW HIRING)

Alphatec Spine

Senior Data Scientist

Carlsbad, CA · On-site

$130K - $150K/yr

The ideal candidate will combine deep technical expertise in predictive modeling and linear algebra ... 000 Full-Time Annual Salary Please note: ATEC Spine does not sponsor employment visas for this ...

Alphatec Spine

Senior Data Scientist

Carlsbad, CA

$130K - $150K/yr

The ideal candidate will combine deep technical expertise in predictive modeling and linear algebra ... 000 Full-Time Annual Salary Please note: ATEC Spine does not sponsor employment visas for this ...

Alphatec Spine

Senior Data Scientist

Carlsbad, CA · On-site

$130K - $150K/yr

The ideal candidate will combine deep technical expertise in predictive modeling and linear algebra ... 000 Full-Time Annual Salary Please note: ATEC Spine does not sponsor employment visas for this ...

Stardock

Senior Graphics Engineer

Plymouth, MI · On-site

We are currently seeking a full-time Senior Graphics Engineer to work on our next generation game ... Strong proficiency in 3D math, linear algebra, shaders, HLSL/GLSL, physically based rendering ...

Stardock Corporation

Senior Graphics Engineer

Plymouth, MI · On-site

$100K - $200K/yr

We are currently seeking a full-time Senior Graphics Engineer to work on our next generation game ... Strong proficiency in 3D math, linear algebra, shaders, HLSL/GLSL, physically based rendering ...

Astrion

RF Signatures Engineer

Huntsville, AL · On-site

$120K - $160K/yr

Huntsville, Alabama Job Status: Full Time Clearance: Secret, TS/SCI preferred SEG, a subsidiary of ... Mathematical background in linear algebra, differential equations, complex analysis, numerical ...

Astrion

RF Signatures Engineer

Huntsville, AL · On-site

Huntsville, Alabama Job Status: Full Time Clearance: Secret, TS/SCI preferred SEG, a subsidiary of ... Mathematical background in linear algebra, differential equations, complex analysis, numerical ...

Garmin

Senior Software Engineer- GNSS Receiver

Brea, CA

$134K - $167K/yr

We are looking for a full-time Senior Software Engineer in our Salem, OR location who is interested ... Strong analytical skills and mathematics fundamentals including linear algebra, probability, and ...

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How much do full time linear algebra jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for full time linear algebra in the United States is $28.85, according to ZipRecruiter salary data. Most workers in this role earn between $27.40 and $30.29 per hour, depending on experience, location, and employer.

What is the difference between Full Time Linear Algebra vs Data Analyst?

AspectFull Time Linear AlgebraData Analyst
Required CredentialsBachelor's or higher in Mathematics, Linear Algebra, or related fieldsBachelor's in Statistics, Mathematics, or related fields; often requires data analysis certifications
Work EnvironmentResearch labs, academic institutions, or technical departmentsBusiness offices, tech companies, or consulting firms
Industry UsageAcademic research, education, or specialized technical rolesBusiness intelligence, marketing, finance, and operations
Common Search/ComparisonFull Time Linear Algebra vs Data Analyst

While Full Time Linear Algebra focuses on theoretical and applied mathematical concepts, Data Analysts utilize these skills to interpret data and support decision-making in various industries. Both roles often require strong analytical skills and familiarity with data tools, but their primary applications and work environments differ.

What are the key skills and qualifications needed to thrive as a Linear Algebra Instructor, and why are they important?

To thrive as a Linear Algebra Instructor, you need a solid background in mathematics, typically with at least a master's degree in math or a related field, and experience in teaching or tutoring. Familiarity with educational technology tools such as learning management systems (LMS), digital whiteboards, and software like MATLAB or Python (NumPy) is often required. Strong communication, patience, and the ability to explain complex concepts clearly are essential soft skills. These qualifications ensure effective instruction, student engagement, and successful learning outcomes in both in-person and online educational environments.

What are Full Time Linear Algebra jobs?

Full Time Linear Algebra jobs are positions that require a strong understanding of linear algebra concepts and techniques, typically applied in areas such as data science, engineering, research, and finance. These roles often involve working with matrices, vectors, and algorithms to solve complex problems, analyze data, or develop mathematical models. Common job titles include data scientist, machine learning engineer, quantitative analyst, and research scientist. Working full-time in such roles usually means a standard 40-hour work week with benefits and opportunities for career advancement. Employers often look for candidates with a background in mathematics, computer science, or engineering.

What are some common challenges faced by professionals working full-time in linear algebra roles, and how can they be addressed?

Professionals in full-time linear algebra roles often encounter challenges such as translating complex theoretical concepts into practical applications, especially when working with large datasets or real-time systems. Collaborating with interdisciplinary teams, such as software engineers or data scientists, can require clear communication to bridge knowledge gaps. Staying updated with the latest computational tools and algorithms is also essential. These challenges can be addressed by participating in ongoing professional development, actively seeking feedback from colleagues, and leveraging open-source resources or collaborative platforms to enhance both technical and teamwork skills.
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Full Time Linear Algebra jobs near you

Member Of Technical Staff - Extreme-Scale Sparse Linear Algebra, Domain Decomposition & GPU Solve...

Vinci AI

Palo Alto, CA • On-site

$100K - $220K/yr

Full-time

Posted 12 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