Augury
Industrial AI
MLOpsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“ML Ops Engineer at Augury. Skills: MLOps, AI systems, Production platform, ML lifecycle. Design production MLOps capabilities. Build systems for experiment tracking”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
5+ years software engineering, 5+ years MLOps, 5+ years ML platform engineering, Python engineering skills, End-to-end ML lifecycle understanding, Experience with large-scale data platforms, Experience with ML platform frameworks, Proven ability to design workflow orchestration, Written and verbal communication skills
Nice to Have
Experience with industrial platforms, Experience with IoT platforms, Experience with manufacturing platforms, Experience with feature stores, Experience with model registries, Experience with dataset versioning, Experience with lineage systems, Experience with AI agents, Experience with RAG systems, Experience with production GenAI applications, Experience with evaluation frameworks
What You'll Do.
Design production MLOps capabilities
Build systems for experiment tracking
Build systems for artifact management
Build systems for reproducibility
Build systems for versioning
Build systems for lineage
Build systems for promotion workflows
Build systems for production readiness
Develop reusable platform tooling
Develop engineering standards
Build operational infrastructure for LLM
Build operational infrastructure for agentic systems
Design evaluation frameworks for AI systems
Design monitoring frameworks for AI systems
Build large-scale training pipelines
Write Python services
Write platform libraries
Drive engineering quality
Implement automated testing
Implement observability
Implement deployment standards
Implement operational best practices
How You'll Work.
Team & Collaboration
Across teams
Communication Scope
Written communication; Verbal communication
Full Job Description
Our mission is to transform how people and machines work together to push the boundaries of human productivity. A leader in Industrial AI, Augury helps the world’s manufacturers leverage real-time production insights to drive new levels of efficiency. Combining predictive and prescriptive AI technology with industry expertise, production teams can proactively address alerts, minimize downtime, reduce asset costs, and maximize yield and capacity. Our customers achieve payback in six months or less, enabling global scale. We're looking for team members excited to partner with the world's manufacturers and build the future of production together. We are looking for a MLOps Engineer with strong production engineering experience building and operating scalable ML and AI systems. This is a software-first MLOps platform role focused on production reliability, ML lifecycle management, large-scale training infrastructure, operational AI systems, and reusable platform capabilities. You will help build and scale the production platform behind Augury’s Industrial AI Workforce, enabling teams across the company to develop, evaluate, deploy, and operate ML and AI systems consistently and safely. A Day In Your Life Design and evolve production MLOps capabilities across the full ML lifecycle including datasets, features, models, evaluations, deployments, monitoring, retraining, and feedback signals. Build systems for experiment tracking, artifact management, reproducibility, versioning, lineage, promotion workflows, and production readiness. Develop reusable platform tooling, golden paths, and engineering standards that improve consistency and delivery velocity across teams. Build operational infrastructure for LLM and agentic systems including prompts, tools, traces, evaluations, observability, safety boundaries, and production monitoring. Design evaluation and monitoring frameworks for AI systems including answer quality, latency, grounding, reliability, and operational regressio
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