At NVIDIA, we pride ourselves on data-driven decision-making, and the data science platform team is at the heart of this initiative. We are looking for an excellent Sr. ML Platform Engineer with expertise in AI, MLOps, cloud computing, and GPU acceleration! Our platform serves as the basis for advanced real time data analytics, streaming, data lake and sophisticated ML/AI training with offline/online inferencing for NVIDIA's cloud services like Cloud gaming, Cloud Deep Learning, Autonomous Vehicles, Omniverse etc. As a ML Platform Engineer, you'll design and build enterprise-level AI solutions using groundbreaking NVIDIA technology. You'll work with internal engineering teams to deploy and operationalize AI at scale by driving adoption for end-to-end Machine Learning and Deep Learning solutions in the cloud!What you'll be doing:Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platformsUsing your skills in AI, MLOps, ML engineering, DevOps, Kubernetes, and orchestration to deploy serverless solutionsCreating microservices for task-specific AI cloud servicesImproving service reliability, observability, develop UI and APIs to improve user experienceWhat we need to see:5+ years of foundational expertise in Engineering, Computer Science, Data Science, or a related fieldBS or MS in Engineering, Mathematics, Physics, Computer Science, or equivalent experienceBasic understanding of ML/DL training and inferencing conceptsEstablished track record working with AI/MLOps GPU accelerated solutions in cloud computing environments including AWS, GCP, and AzureExperience with virtualization and cluster management tools, including Docker/Containers, KubernetesStrong analytical and problem-solving skillsAbility to multitask efficiently in a wide-ranging environmentClear written and oral communication skills with a strong desire to share knowledge with clients, partners, and co-workersWays to stand out from the crowd:Strong coding and debugging skills, including experience with Python, Java, GoProven expertise through projects or Open Source contributions in cloud-based GPU workloads, Kubernetes, or other related areasExperience with AI frameworks and tools on GPUsBackground with serverless computingNVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!NVIDIA is committed to fostering a diverse 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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