Overview:
This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world’s most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

“THE REAL DIFFERENTIATOR IS DDN. I NEVER HESITATE TO RECOMMEND DDN. DDN IS THE DE FACTO NAME FOR AI STORAGE IN HIGH PERFORMANCE ENVIRONMENTS” - MARC HAMILTON, VP, SOLUTIONS ARCHITECTURE & ENGINEERING | NVIDIA

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence.
Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management.
Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage.
Job Description:
As a AI Solutions Specialist at DDN, you will lead the technical development of cutting-edge AI, GPU virtualization, and high-performance computing (HPC) solutions. You will play a critical role in optimizing our storage and cluster environments to drive AI inferencing, GPU computing, and large-scale HPC systems to new heights. You will leverage your deep technical expertise in AI inference, GPU virtualization, and infrastructure optimization to enable seamless integration of our storage products with modern computing stacks.
Your work will impact our customers’ ability to run AI-driven workloads and maximize performance across hybrid on-premise and cloud environments. You’ll collaborate with cross-functional teams to innovate, drive strategic partnerships, and ensure the scalability and efficiency of AI and HPC solutions for some of the most demanding applications in the world.

REQUIRED SKILLS AND EXPERIENCE:

• Extensive experience in optimizing AI inference and GPU-based workloads using frameworks such as TensorFlow, PyTorch, and CUDA. Strong understanding of GPU virtualization, including integration of technologies such as NVIDIA vGPU and GPUDirect.
• Proven track record of managing large-scale HPC clusters, optimizing performance, and scaling workloads. Proficient in cluster management tools and optimizing infrastructure for AI-driven applications.
• Expertise in deploying cloud-based solutions across hybrid environments (AWS, Azure, Google Cloud, etc.). Experience in managing and optimizing cloud-native infrastructure for real-time AI and HPC workloads.
• Knowledge of RDMA, InfiniBand, high-bandwidth interconnects, and their impact on performance in distributed systems.
• Extensive experience working with Nvidia GPUs. Familiarity with Nvidia’s software stack and optimizations for AI/ML workloads.
• Programming (e.g., Python, C++, CUDA) and performance tuning for large-scale, complex systems. Experience optimizing LLM (Large Language Model) training and inference workloads.

PREFERRED QUALIFICATIONS:

• +5 years of experience
• BS or MS degree in Computer Science, Engineering, or related technical field.
• Experience with distributed systems, containerization (Docker, Kubernetes), and orchestration.
• Familiarity with machine learning and AI frameworks, and the ability to work with data science teams to optimize models.

• LEAD INNOVATION IN GPU VIRTUALIZATION & AI WORKLOADS:Design, optimize, and implement advanced GPU virtualization solutions, including GPU Direct Storage integration, to enhance performance for AI inferencing and HPC workloads.
• OPTIMIZE LARGE-SCALE AI & HPC INFRASTRUCTURES:Develop and deploy solutions that improve cluster utilization and optimize performance for AI and GPU-driven systems. Manage GPU clusters and related infrastructure to maximize availability, scalability, and efficiency.
• AI INFERENCE & MODEL OPTIMIZATION:Drive the optimization of AI inference workloads using frameworks such as TensorFlow, PyTorch, and other industry-leading tools. Leverage expertise in CUDA to tune and accelerate AI models and workloads.
• HYBRID CLOUD INFRASTRUCTURE STRATEGY:Architect, deploy, and optimize cloud-based and hybrid on-premise solutions for AI and HPC workloads. Ensure integration with cloud providers and bare-metal systems to deliver high-performance, scalable, and cost-effective solutions.
• DRIVE PERFORMANCE IMPROVEMENT:Continually assess and optimize system configurations for AI inference and HPC workloads, driving significant performance improvements through specialized technologies such as RDMA, InfiniBand, and high-bandwidth interconnects.
• STRATEGIC PLANNING & PARTNERSHIPS:Build and maintain relationships with key stakeholders, including cloud service providers, hardware manufacturers (e.g., Nvidia), and customers, to stay ahead of industry trends and integrate best-in-class technologies into DDN’s offerings.