Senior Machine Learning Engineer, Accelerated Apache Spark

NVIDIA; Santa Clara (CA); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Machine Learning Engineer to join the GPU accelerated Apache Spark team, focusing on performance prediction and optimization of GPU accelerated enterprise Apache Spark workloads. You will apply the latest ML/AI methods, mentor engineers, and collaborate with partners on deployment across environments, while staying current with advances in ML systems.

The base salary range is 224,000 USD - 356,500 USD, with equity and benefits offered.

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+ 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).

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.

Skills

Python

Spark

ML/DL

GenAI

Reinforcement Learning

Feature Engineering

XGBoost

Leadership

Education

BS/MS/PhD in ML/DS/CS

Job description

NVIDIA is looking for a Machine Learning Engineer to join the GPU accelerated Apache Spark team. Apache Spark is the most popular data processing engine in data centers for running massive 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 very large Apache Spark applications. 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.
• 3+ 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 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 5, 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.

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