NVIDIA is seeking a Machine Learning Engineer to join the GPU accelerated Apache Spark team. This role focuses on enhancing the performance of Apache Spark workloads using NVIDIA GPUs. The engineer will collaborate with the open source community and apply advanced machine learning methods to optimize enterprise applications. The position requires a blend of technical expertise and leadership in machine learning and data science.

• 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 a technical lead in ML model development.
• Proven hands-on experience (2+ years) with large-scale data processing platforms, such as Apache Spark.
• 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).

• 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.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.