Lead MLOps Engineer

Milwaukee Electric Tool

  • Menomonee Falls, WI
  • Permanent
  • Full-time
  • 1 month ago
Job Description:INNOVATE without boundaries!At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success -- so we give you unlimited access to everything you need to provide support to your business unit.Our people and our culture are the secrets to our success. We empower you to own it, drive it, and do what it takes to support the biggest breakthroughs in the industry. As we expand our machine learning capabilities, we’re looking for a Lead MLOps Engineer to build and scale our ML infrastructure from the ground up with a strong focus on collaborating with domain experts embedded in business units and engineering teams, treating them as internal customers to ensure scalable solutions.*Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position.Your Role on Our Team:As an MLOps Engineer at Milwaukee Tool, you will lead the design, deployment, and governance of our machine learning operations. You’ll work closely with and empower ML engineers and data scientists across teams using Databricks, Azure, Citrine and AWS to unify and streamline model development, deployment, and monitoring. This is a hands-on role with broad technical ownership and the opportunity to shape our MLOps strategy and tooling from scratch.You’ll be DISRUPTIVE through these duties and responsibilities:
  • Architect and implement scalable MLOps infrastructure across Databricks, Azure, and AWS.
  • Build and maintain CI/CD/CT pipelines for model training, validation, deployment, and monitoring.
  • Collaborate with developers to establish best practices for model versioning, reproducibility, and governance.
  • Implement observability tools to monitor model performance, drift, latency, and system health.
  • Collaborate with ML engineers, data scientists, electrical engineers and DevOps to integrate models into production systems.
  • Work with ML community to define and enforce security, compliance, and privacy standards across the ML lifecycle.
  • Document and promote MLOps best practices and tooling.
  • Continuously evolve ML ops pipelines to support the ML pipelines for both internal IT and end user solutions.
  • Drive awareness and adoption of existing ML tools and platforms across the organization through documentation, training, and internal community engagement.
The TOOLS you’ll bring with you:
  • 5+ years of experience in MLOps, DataOps, DevOps, or backend engineering roles.
  • Experience with Databricks ML services, SageMaker, Azure ML.
  • Strong Python skills and familiarity with ML frameworks (e.g., PyTorch, MLflow).
  • Experience with infrastructure-as-code (Terraform, Spacelift, GitHub Actions, Databricks Asset Bundles, Azure Pipelines) and container orchestration (Docker, Kubernetes).
  • Proven ability to build CI/CD pipelines and model registries from scratch.
  • Familiarity with monitoring tools (e.g., Azure Synapse Monitoring, Azure ML Studio monitoring, Databricks Lakehouse Monitoring, CloudWatch, CloudTrail).
  • Hands-on experience with model and data quality monitoring.
  • Strong understanding of the ML lifecycle, from data ingestion to model deployment strategies and retraining.
  • Experience supporting multi-cloud environments and cross-functional collaboration.
  • Experience maintaining ops pipelines for end user facing solutions, ideally in situations where access to data and/or deployed models may be limited.
Other TOOLS we prefer you to have:
  • Experience with GenAI/LLMOps workflows and prompt management.
  • Knowledge of security and compliance in regulated environments.
  • Experience deploying ML models to edge devices and working with C/static datatypes in embedded environments.
  • Familiarity with ML service Citrine, data governance and lineage tools.
  • Experience with performance testing, observability, and cost optimization for ML workloads.
  • Familiarity with transformer-based architectures and LLM frameworks (e.g., Hugging Face, OpenAI, LangChain) including prompt orchestration and autonomous agent flows.
Working Conditions:The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
  • Frequently required to stand, walk, bend, stretch, reach, and effectively communicate with others in the workplace
  • Sitting for prolonged periods of time
  • Prolonged exposure to computer screens
  • Repetitive use of hands and fingers to operate office equipment, machinery, hand tools and/or power tools
  • Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus
  • May require to wear personal protective equipment which includes, but is not limited to, safety glasses, gloves, and hearing protection
  • May work in laboratories and/or controlled, enclosed, restricted areas
  • Noise levels range from moderate to loud
  • Must be able to lift up to 50 pounds at a time
  • May require travel dependent on company needs
We provide these great perks and benefits:
  • Robust health, dental and vision insurance plans
  • Generous 401 (K) savings plan
  • Education assistance
  • On-site wellness, fitness center, food, and coffee service
  • And many more, check out our benefits site
.Milwaukee Tool is an equal opportunity employer.

Milwaukee Electric Tool