MTS - AI / MLOps
Everpure · Posted Oct 6
Enterprise data storage and management platform for apps, analytics, and AI
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About the role
Everpure (formerly Pure Storage) is a data platform company whose strategic agenda spans hyperscalers, AI labs, the AI hardware supply chain, and the broader AI ecosystem. The Pure Solutions team architects enterprise-grade AI/ML solutions that integrate Pure Storage platforms with the open-source MLOps ecosystem such as Kubeflow, MLflow, and Ray. This senior MLOps solutions engineering role owns end-to-end MLOps pipelines, GPU inference optimization, AI/ML reference architectures, and technical enablement for sales and partners.
What you will 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.
Skills used in this role
What the employer is looking for
- 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.
Benefits and support
- Flexible time off
- Wellness resources
- Company-sponsored team events
About Everpure
Everpure is an enterprise data storage and management company that unifies all data with an enterprise data cloud, making it easy to manage and get AI-ready fast. Formerly known as Pure Storage, the company delivers an industry-leading, ever-evolving storage and data management platform.
- Industry
- Data Storage
- Company size
- 6000+ employees
- Founded
- 2009
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company · $470M raised
- 2013-08-29Series E$150M
- 2014-04-23Series F$225M
Leadership
Chairman and CEO
Rob Lee
Chief Technology Officer
Dan FitzSimons
Chief Revenue Officer
Recent coverage
PRNewswire
Everpure's Expanding Business Model Fuels New Long-Term OutlookSeptember 23, 2026
PRNewswire
Everpure to Join the S&P 500September 8, 2026
Computer Weekly
Everpure Channel Boss Encouraging Partners to Seize AI-Fuelled OpportunitiesOctober 1, 2026