NVIDIA
Senior Machine Learning Engineer, Accelerated Apache Spark
$224K–$356K
US, CA, Santa Clara · Senior · Full-time · Posted Sep 1, 2026
- Experience
- 12+ years in ML/DL solution development and productionization; 3+ experience as an ML model development technical lead; 2+ years with large-scale data processing platforms.
- Education
- BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science, or a closely related field.
About the job
Designs machine learning systems that predict and optimize GPU-accelerated Apache Spark workloads, helping enterprises migrate and run workloads at scale.
What you'll do
- Build ML solutions, algorithms, and adaptive systems to improve Spark performance on GPUs.
- Develop AI-based agents and tools for system troubleshooting and application optimization.
- Collaborate with partners and customers on deploying ML solutions, and provide technical mentorship to engineers.
What they ask for
- 12+ years of professional experience designing, implementing, and productionizing ML/DL solutions.
- 3+ experience as technical lead in ML model development.
- 2+ years of hands-on experience with large-scale data processing platforms such as Apache Spark.
- Strong Python programming and experience with ML methodologies, feature engineering, and boosted tree models.
Nice to have
- Understanding of Apache Spark internals and architecture; familiarity with NVIDIA GPUs and CUDA.
- Experience coding in Scala, Java, and/or C++.
Pay
224,000 USD - 356,500 USD (base salary)
Tools
Apache Spark, Python, numpy, pandas, scikit-learn, scipy, pytorch, tensorflow
AI focus
Applies ML/AI to predict and optimize GPU-accelerated Spark workloads; develops adaptive systems and AI-based agents for troubleshooting and optimization. Relevant methods include LLM/GenAI, reinforcement learning, and adaptive online ML.
Model-written summary · the original posting is authoritative