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Home Based Nvidia Machine Learning Jobs in California

Machina Labs

Machine Learning Engineer

Los Angeles, CA · On-site

Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that ... Duties and responsibilities may change based on business needs. The base salary range for this role ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that ... Duties and responsibilities may change based on business needs. $160,000 - $190,000 a year The base ...

Amat

Physicist/Scientist Machine Learning

Santa Clara, CA · On-site +1

$138K - $190K/yr

Focus will be on developing ML models based on plasma and electromagnetic simulations. This role is ... Experience with NVIDIA Physics NeMo , NVIDIA Modulus, or related physicsinformed or ...

Nvidia

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$143K - $189K/yr

... both machine learning fundamentals and software architecture & engineering. What you'll be doing ... Collaborate with teams across NVIDIA to use performant kernel implementations within the automated ...

NVIDIA

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$142K - $188K/yr

... both machine learning fundamentals and software architecture & engineering. What you'll be doing ... Collaborate with teams across NVIDIA to use performant kernel implementations within the automated ...

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Principal Machine Learning Engineer, Accelerated Apache Spark

Principal Machine Learning Engineer, Accelerated Apache Spark

Nvidia

Santa Clara, CA

$158K - $212K/yr

Full-time

Posted 21 days ago

Job description

NVIDIA is looking for a Machine Learning (ML) Engineer to join the GPU accelerated Apache Spark team. Apache Spark is the most popular data processing engine in data centers for running large scale workloads for ETL, SQL, and ML/DL model training and inference pipelines, spanning many domains and use cases. NVIDIA GPUs offer a promising avenue for significantly speeding up and/or lowering the cost of running Apache Spark applications at massive scales. You will work with the open source community to accelerate Apache Spark with GPUs. You will apply the latest ML/AI methods to empower enterprises to migrate Spark workloads onto GPUs at scale.

What you'll be doing:

  • Design and implement machine learning solutions for performance prediction and optimization of GPU accelerated enterprise Apache Spark workloads.

  • Develop advanced algorithms and adaptive systems to continuously improve the performance of Apache Spark workloads on GPUs.

  • Develop AI-based agents and tools to assist with fixing system issues and application optimization.

  • Collaborate with key partners and customers on the deployment of complex machine learning solutions in various environments.

  • Maintain deep domain expertise by knowing the latest published advances in ML systems and algorithms.

  • Provide technical mentorship and leadership in data science and machine learning to a team of engineers.

What we need to see:

  • BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science or a closely related field.

  • 12+ years of professional experience in designing, implementing, and productionizing high-quality ML/DL solutions.

  • 5+ experience as technical lead in ML model development.

  • Proven hands-on experience (2+ years) with large-scale data processing platforms, such as Apache Spark.

  • Proven ability to employ modern tooling and sound techniques for all aspects of crafting, deploying, and maintaining machine learning models.

  • Excellent programming skills in Python and Python data science related libraries like numpy, pandas, scikit-learn, scipy, pytorch, and tensorflow.

  • Deep experience with sophisticated ML methodologies, including LLM/GenAI, reinforcement learning, and adaptive, on-line ML systems.

  • Strong expertise in feature engineering, feature importance assessment, and developing boosted tree model solutions (e.g., XGBoost).

Ways to stand out from the crowd:

  • Understanding of the internal workings and architecture related to Apache Spark.

  • Familiarity with NVIDIA GPUs and CUDA.

  • Experience coding in Scala, Java, and/or C++.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most experienced and dedicated people in the world working for us. If you are passionate about what you do, creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 25, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.
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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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