MLOps Platform Engineer, dv01

• A senior cloud and platform engineer: You have 8+ years of experience in cloud infrastructure, DevOps, or platform engineering roles, with deep expertise designing and operating distributed systems in production
• Experienced with MLOps and agentic platforms: You have direct exposure to ML/GenAIOps practices, such as monitoring, anomaly detection, predictive alerting, or automated remediation, applied to real production systems
• 5+ years of MLOps experience is required
• Strong in cloud-native infrastructure:
• You are proficient in building and managing cloud environments, Kubernetes, containerized workloads and infrastructure-as-code tools such as Terraform
• Comfortable supporting AI workloads:
• You have hands-on experience supporting platforms that and host/run deep neural networks, including LLM runtimes (e.g., vLLM, llama.cpp), ML compiler stacks (e.g., LLVM/MLIR), and PyTorch-based production systems
• Security- and operations-minded: You have a strong understanding of infrastructure security, IAM, secrets management, and operational risk as it relates to AI-enabled systems
• A platform-focused technical leader:
• You operate effectively as a technical leader, influencing architecture and standards while remaining hands-on
• You communicate clearly, collaborate well cross-functionally, and thrive in ambiguous problem spaces
• Forward-thinking and pragmatic: You are proactive and innovative, with the ability to introduce emerging agentic patterns while balancing operational maturity and long-term maintainability
• You will help design and operate scalable benchmarking and evaluation frameworks for agentic AI systems, enabling quantitative measurement of accuracy, reliability, cost–performance tradeoffs, regression detection, and the impact of model, prompt, or architecture changes (including techniques such as LLM-as-a-judge), with tooling that is reusable and accessible across the organization

Desirable

• Build and operate an AI infrastructure platform:
• You will design, build, and operate cloud-native infrastructure and platform tooling that accelerates AI development across the company. This includes enabling teams to develop, deploy, and operate AI-powered services safely and efficiently in production environments
• Own the DevOps and infrastructure side of MLOps and Agentic Systems:
• You will focus on the operational foundations of AI systems, including CI/CD for AI workloads, scalable inference infrastructure, observability, cost management, and reliability. You will establish repeatable patterns and shared services that reduce friction for teams building AI-enabled applications
• Enable AI services, agents, and runtime platforms:
• You will build and maintain infrastructure to support AI services such as LLM-backed APIs, Model Context Protocol (MCP) servers, and agentic systems used by production applications. You will enable secure tool access, runtime orchestration, and isolation boundaries for AI-driven workloads
• Integrate MLOps capabilities into platform operations:
• You will apply MLOps concepts to improve platform operations, including using AI-driven approaches for monitoring, alerting, anomaly detection, and incident response across AI and non-AI systems. You will help evolve how the platform observes and operates complex AI-enabled systems at scale
• Establish governance, security, and operational guardrails:
• You will help define and implement infrastructure-level governance for AI systems, including access controls, deployment policies, auditability, and secure-by-default patterns. You will partner with security and compliance teams to ensure AI infrastructure aligns with organizational risk and regulatory requirements
• Provide technical leadership and enablement:
• You will act as a technical leader, influencing platform architecture and best practices across teams. You will mentor engineers and work closely with product, data, and application teams to align AI platform capabilities with business goals
• Contribute to dv01’s AI and data roadmap
• Establish technical direction and strategy
• Mentor and provide technical guidance to junior engineers