Senior Solutions Engineer - MLOps at Pure Storage

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

02 Mar, 26

Salary

0.0

Posted On

02 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, Python, Deep Learning, GPU Computing, Kubernetes, Infrastructure as Code, CI/CD, Data Science, AI, MLflow, Kubeflow, NVIDIA Triton Inference Server, Ansible, Terraform, High-Performance Storage, Distributed Training

Industry

IT Services and IT Consulting

Description

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pure Solutions team as a Senior MLOps Solutions Engineer to architect and build high-scale, enterprise-grade AI/ML solutions. You will be instrumental in integrating Pure Storage platforms with the evolving open-source MLOps ecosystem (Kubeflow, MLflow, Ray) to operationalize the complete machine learning lifecycle. This role requires a creative technologist with deep Python expertise to drive innovation and enable our customers and partners to achieve production AI success. WHAT YOU'LL DO Design and Automate MLOps Pipelines: Lead the development of end-to-end MLOps workflows using CI/CD tools (Git/Jenkins) and orchestration platforms (MLflow/Kubeflow), specifically integrating Pure Storage's FlashBlade, FlashArray, and Portworx as the high-performance data plane for data ingestion, training, and inference. Build High-Performance AI/ML Reference Architectures: Create validated, repeatable deployment models using Infrastructure as Code (e.g., Ansible, Terraform) for AI/ML environments spanning bare metal, virtual machines, and GPU-accelerated Kubernetes clusters, ensuring optimal performance for distributed training. Optimize and Operationalize GPU Inference: Architect and implement solutions for high-throughput, low-latency model serving, utilizing technologies like NVIDIA Triton Inference Server and advanced optimization techniques (quantization, model sharding like DeepSpeed/Megatron-LM, and dynamic batching) for large models (LLMs). Enable Sales and Drive Ecosystem Adoption: Develop automated, GPU-enabled MLOps lab environments, high-quality technical documentation, and live demonstrations to enable global sales, field engineering teams, and strategic partners on new AI integrations, directly impacting solution adoption and revenue. Define Strategic MLOps Direction: Collaborate closely with Data Scientists and Product Management to influence the technical strategy for AI platform integrations and provide essential input into future product roadmaps related to accelerated compute and high-performance storage requirements. WHAT YOU BRING Deep MLOps Pipeline & Infrastructure as Code (IaC) Expertise: Hands-on experience designing, building, and automating MLOps workflows using orchestration tools (e.g., Kubeflow, MLflow, Vertex AI, SageMaker) and proficiency with IaC tools such as Terraform or Ansible. Advanced Python & Deep Learning Framework Proficiency: Expert-level skills in Python for Data Science and MLOps, including libraries like pandas and NumPy, and demonstrated experience with Deep Learning frameworks, particularly PyTorch, focusing on distributed training and model handling. Expertise in GPU-Accelerated Computing & Container Orchestration: Strong practical knowledge of GPU computing principles (CUDA), technologies like NVIDIA Triton Inference Server, and expert-level working knowledge of Kubernetes for GPU resource management, scheduling, and persistent storage for containers. High-Performance Storage and Data Center Understanding: Solid comprehension of high-performance data center infrastructure, including high-speed networking (e.g., RoCE, 100GbE), and storage platforms optimized for high-throughput, low-latency AI/ML workloads (e.g., high-performance S3, parallel file systems). We are primarily an in-office environment and therefore, you will be expected to work from the {{OFFICE_LOCATION}} office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave. WHAT YOU CAN EXPECT FROM US: Pure Innovation: We celebrate those who think critically, like a challenge and aspire to be trailblazers. Pure Growth: We give you the space and support to grow along with us and to contribute to something meaningful. We have been Named Fortune's Best Large Workplaces in the Bay Area™, Fortune's Best Workplaces for Millennials™ and certified as a Great Place to Work®! Pure Team: We build each other up and set aside ego for the greater good. And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources and company-sponsored team events. Check out purebenefits.com for more information. ACCOMMODATIONS AND ACCESSIBILITY: Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this, contact us at TA-Ops@purestorage.com if you’re invited to an interview. OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM: We’re forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isn’t just accepted but embraced. That’s why we are committed to fostering the growth and development of every person, cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership. Pure is proud to be an equal opportunity and affirmative action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire. JOIN US AND BRING YOUR BEST. BRING YOUR BOLD. BRING YOUR FLASH.

Responsibilities

Architect and build high-scale, enterprise-grade AI/ML solutions while integrating Pure Storage platforms with the open-source MLOps ecosystem. Lead the development of end-to-end MLOps workflows and create validated deployment models for AI/ML environments.