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Senior Machine Learning Engineer, Accelerated Apache Spark

NVIDIA· Engineer, Sys SW
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Santa Clara, CA$224k - $356.5k + equityFull-timePosted 1mo ago

About the role

Machine Learning Engineer to join NVIDIA's GPU accelerated Apache Spark team, applying ML/AI methods to accelerate Spark workloads on GPUs, and developing AI-based tools for performance optimization and issue fixing.

Responsibilities

  • 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.

Qualifications

  • 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.
  • 3+ years of experience as technical lead in ML model development.
  • 2+ years of hands-on experience 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).

Skills

Required:Machine Learning / ML engineeringLarge-scale data processing (Apache Spark)Python and data science librariesLeadership / technical leadFeature engineering and tree-based models
Nice to have:GenAI / RL / online MLScala/Java/C++ (standout)

Benefits

  • equity
  • benefits (per NVIDIA)
Last updated Sep 4, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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