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Virtual Scientific Computing Jobs in California (NOW HIRING)

Lam Research Corporation

Process Engineer 3

Fremont, CA · On-site

$104K - $192K/yr

Highly proficient in MATLAB, Python, or other similar scientific computing language. * Working ... Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier ...

Lam Research Corporation

Process Engineer 4

Fremont, CA · On-site

$104K - $231K/yr

Highly proficient in MATLAB, Python, or other similar scientific computing language. * Working ... Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier ...

Lam Research Corporation

Process Engineer 3

Fremont, CA · On-site

$86K - $192K/yr

Highly proficient in MATLAB, Python, or other similar scientific computing language. * Working ... Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier ...

Lam Research Corporation

Process Engineer 3

Fremont, CA · On-site

$86K - $192K/yr

Highly proficient in MATLAB, Python, or other similar scientific computing language. * Working ... Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier ...

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Virtual Scientific Computing information

What is virtual scientific computing?

Virtual scientific computing refers to the use of cloud-based or remote computational resources to perform scientific research and analysis. Instead of relying solely on local hardware, scientists access high-performance computing environments, data storage, and specialized software through the internet. This approach enables greater flexibility, scalability, and collaboration, allowing researchers to run complex simulations, analyze large datasets, and share results with colleagues worldwide. Virtual scientific computing is widely used in fields such as physics, chemistry, biology, and engineering.

What are some typical challenges faced by professionals in virtual scientific computing roles, and how can they be addressed?

Professionals in Virtual Scientific Computing often encounter challenges such as managing large-scale simulations, ensuring computational accuracy, and optimizing performance across diverse hardware architectures. Collaborating effectively with multidisciplinary teams—such as scientists, engineers, and IT specialists—can also be complex due to varying technical backgrounds. Addressing these challenges usually involves continuous learning, leveraging robust collaboration tools, and staying updated on the latest computational methods and best practices to ensure efficient and accurate results.

What are the key skills and qualifications needed to thrive in virtual scientific computing?

To thrive in Virtual Scientific Computing, you need a solid background in mathematics, programming (often Python, C++, or MATLAB), and computational science, typically supported by a relevant degree. Familiarity with high-performance computing (HPC) environments, cloud computing platforms, and simulation software is commonly required. Strong analytical thinking, problem-solving ability, and effective collaboration are vital soft skills for excelling in multidisciplinary teams. These competencies are crucial for efficiently solving complex scientific problems and advancing research using computational methods.
What are the most commonly searched types of Scientific Computing jobs in California? The most popular types of Scientific Computing jobs in California are:
What are popular job titles related to Virtual Scientific Computing jobs in California? For Virtual Scientific Computing jobs in California, the most frequently searched job titles are:
What job categories do people searching Virtual Scientific Computing jobs in California look for? The top searched job categories for Virtual Scientific Computing jobs in California are:
What cities in California are hiring for Virtual Scientific Computing jobs? Cities in California with the most Virtual Scientific Computing job openings:
Virtual Scientific Computing jobs near you

Engineering Manager, AI Compiler Analysis

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

NVIDIA's invention of the GPU transformed computer graphics, parallel computing, and modern AI. Today, NVIDIA high-performance processing platforms power breakthroughs across generative AI, autonomous systems, scientific computing, robotics, and high-performance data centers.
NVIDIA's compiler technologies are key enablers of AI at scale, turning rapidly evolving deep learning models into highly optimized GPU programs for training and inference. As AI models, GPU architectures, and compiler systems become more sophisticated, AI compiler quality has become a deep technical challenge at the intersection of compilers, machine learning frameworks, numerical computing, formal reasoning, and large-scale systems engineering. To address these complex challenges, we are seeking an Engineering Manager to spearhead our strategy for verifying AI compilers built for next-generation deep learning workloads. This is a hands-on compiler engineering leadership role for someone who understands where compiler quality can regress in modern AI compiler stacks.
What You'll Be Doing:
  • Lead, mentor, and grow a highly technical team responsible for AI compiler verification.
  • Own the verification of next-generation AI workloads, including LLMs and agentic AI systems, across the full spectrum of the AI compiler stack and execution pipeline.
  • Define formal-verification requirements for AI compiler transformations and generated GPU programs, including formal specifications, tensor/operator semantics, semantic preservation, code equivalence, numerical behavior, and properties stressed by AI-generated or adversarial workloads.
  • Drive the use of AI-assisted and compiler-aware verification techniques, including adversarial workload generation, differential testing, symbolic reasoning, formal methods, fuzzing, static analysis, and automated debugging.
  • Partner closely with AI compiler development, CUDA software, ML framework, runtime, product, and AI software teams to build scalable verification infrastructure, improve engineering velocity, and increase production confidence.

What We Need To See:
  • BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience.
  • 10+ overall years of total relevant software engineering experience, including at least 3 years experience leading engineering teams or major technical initiatives.
  • Experience with AI compiler or framework technologies such as MLIR, TensorRT, XLA, Triton, PyTorch, or JAX.
  • Fluency with AI workload and ML framework concepts, including computation graphs, tensor operations, model execution, and training or inference workflows.
  • Strong people management skills, including hiring, mentoring, performance management, and team development.

Ways To Stand Out From The Crowd:
  • Hands-on with deep learning compiler internals, including compiler IRs, optimization and lowering pipelines, code generation, runtime integration, or production compiler infrastructure.
  • Experience verifying performance-sensitive compiler behavior and root-causing subtle regressions in production AI/ML systems using computational methods, fuzzing, code inspection, or automated debugging.
  • Background in formal verification or programming languages, with familiarity in formal specifications, theorem proving, Lean, SMT/SAT solvers, or symbolic reasoning.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 2, and 200,000 USD - 322,000 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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