Senior MLOps Engineer – DSX Enablement

🔥 0 minutes ago

🏄 California, Washington – Remote

🏄 California – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Develop innovative solutions advancing AI infrastructure capabilities • Advise infrastructure experts on the demands of ML workloads • Help practitioners diagnose and solve full-stack AI and ML system problems • Support internal and external customers’ AI and ML initiatives, including LLM performance evaluation and new hardware in open-source frameworks • 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 • Guide joint engagements, ensure initiative success on DGX Cloud, and solve complex production problems • Collaborate with infrastructure software and accelerated-framework teams • Profile and tune large-scale training and inference workloads on NVIDIA Cloud Partner platforms • Lead efforts to reduce latency, cost, and operational risk • Develop open-source tools and reference architectures for machine learning and AI workloads, pipelines, and systems at scale

🎯 Requirements

• 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 Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale • Solid scripting and programming skills in bash and Python • Solid systems programming skills in 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 articulate architectures, trade-offs, and recommendations to engineering and leadership audiences • A clear record of engineering discipline and execution on interesting projects • Experience contributing to and working in open-source communities • Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, InfiniBand, NVLink, and RoCE • Experience building machine learning systems in a security-critical environment and with distributed training and inference frameworks • Familiarity with MLOps practices in a cloud-native context, including containerization, CI/CD pipelines, workflow automation, observability stacks, and GitOps workflows • Direct experience diagnosing and fixing performance or correctness problems spanning hardware, networking, accelerators, hypervisors or operating systems, compilers or runtimes, application code, and libraries

🏖️ Benefits

• Competitive salaries • Generous benefits package • Equity