NVIDIA is looking for a Senior MLOps Engineer to join the DSX Enablement team, focusing on implementing and enhancing AI workloads for strategic customers. The role involves developing innovative solutions to advance AI infrastructure capabilities and collaborating with both internal and external stakeholders. The engineer will work on full-stack AI and ML system problems, ensuring the success of various AI initiatives. This position offers the opportunity to work with cutting-edge technologies and make a significant impact in the AI domain.

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
• 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally targeting large-scale production systems.
• Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis to production systems.
• Facility with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
• Solid scripting and programming skills in languages like bash and Python and solid systems programming skills in a language like C++, Go, or Rust.
• Experience using machine learning or deep learning frameworks for training and inference.
• Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.
• A clear record of engineering discipline and execution on interesting projects, whether working alone or collaborating on a team.

• Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners, including distributed training, inference optimization, and MLOps pipelines.
• Act as a primary technical contact for internal and external customers and partners, guiding joint engagements and ensuring the success of initiatives on DGX Cloud.
• Work closely with teams building the infrastructure software and accelerated frameworks that support today’s most compelling AI applications.
• Profile and tune large-scale training and inference workloads on NCP platforms, leading efforts to reduce latency, cost, and operational risk.
• Develop open-source tools and reference architectures to facilitate the building and management of machine learning and AI workloads, pipelines, and systems at scale.

• 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.