Senior Machine Learning Engineer, Accelerated Apache Spark

at Nvidia

USD 224,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 7 Algorithms CUDA @ 3 Data Science @ 4 Deep Learning @ 8 ETL GPU GenAI Generative AI @ 7 Java @ 4 LLM Machine Learning @ 4 Pandas @ 6 PyTorch @ 6 Python @ 6 Reinforcement Learning @ 7 SQL Scala @ 4 Spark @ 4 TensorFlow @ 6 XGBoost @ 7 scikit-learn @ 6

Details

NVIDIA is looking for a Machine Learning Engineer to join the GPU-accelerated Apache Spark team.

Apache Spark is a popular data processing engine for running large-scale workloads in data centers, including ETL, SQL, and machine learning and deep learning model training and inference pipelines. NVIDIA GPUs can significantly speed up or reduce the cost of large Apache Spark applications. You will work with the open-source community to accelerate Apache Spark with GPUs and apply the latest machine learning and artificial intelligence methods to help enterprises migrate Spark workloads to GPUs at scale.

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 system issue resolution and application optimization.
Collaborate with key partners and customers on deploying complex machine learning solutions in various environments.
Maintain deep domain expertise by following the latest advances in machine learning systems and algorithms.
Provide technical mentorship and leadership in data science and machine learning to a team of engineers.

Requirements

BS, MS, PhD, or equivalent experience in Machine Learning, Data Science, Computer Science, or a closely related field.
12+ years of professional experience designing, implementing, and productionizing high-quality machine learning and deep learning solutions.
3+ years of experience as a technical lead in machine learning model development.
At least 2 years of hands-on experience with large-scale data processing platforms such as Apache Spark.
Ability to use modern tooling and sound techniques for crafting, deploying, and maintaining machine learning models.
Excellent programming skills in Python and Python data science libraries, including NumPy, pandas, scikit-learn, SciPy, PyTorch, and TensorFlow.
Deep experience with advanced machine learning methodologies, including LLMs and generative AI, reinforcement learning, and adaptive online machine learning systems.
Strong expertise in feature engineering, feature importance assessment, and developing boosted tree model solutions such as XGBoost.

Preferred Qualifications

Understanding of the internal workings and architecture of Apache Spark.
Familiarity with NVIDIA GPUs and CUDA.
Experience coding in Scala, Java, and/or C++.

Compensation and Benefits

The base salary range is USD 224,000–356,500, determined by location, experience, and compensation for employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until September 5, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.