MLOps Lead Engineer
St. Louis, Missouri, United States
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign, automate, and govern end-to-end ML production lifecycles
Lead upskilling initiatives for onsite client engineering teams
Build CI/CD/CT pipelines for ML on Databricks
Set up central governance and real-time observability for ML systems
From the employer’s posting
design, automate, and govern end-to-end ML production lifecycles
leading upskilling initiatives for onsite engineering teams
continuous integration and deployment (CI/CD/CT)
central governance, and real-time observability
What you’ll bring
All qualificationsCore experience
- Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations.
Qualification wording
Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations.
Tools in this posting
- Python
- AWS
- Azure
- Databricks
- Delta Lake
- MLflow
- PySpark
Source — Tool mentions in context
- Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. - Core Technical Stack: Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python. - Automation & DevOps: Strong experience building automated CI/CD/CT pipelines using Databricks Asset Bundles (DABs), Azure DevOps, or GitHub Actions.
- Core Technical Stack: Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python. - Automation & DevOps: Strong experience building automated CI/CD/CT pipelines using Databricks Asset Bundles (DABs), Azure DevOps, or GitHub Actions. - Governance & Security: Deep understanding of enterprise security controls, secret management (Key Vault/KMS), and multi-environment deployment isolation.
We are seeking an experienced MLOps Lead Engineer to take full ownership of our enterprise Machine Learning operations on the Databricks Lakehouse platform. In this role, you will design, automate, and govern end-to-end ML production lifecycles—spanning continuous integration and deployment (CI/CD/CT), central governance, and real-time observability. You will act as the principal technical authority, bridging platform engineering with client-side operations by leading upskilling initiatives for onsite engineering teams. Requirements
Required Qualifications & Experience - Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations. - Core Technical Stack: Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python.
Posting record
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- Live
- First seen by us
- Aug 26, 2026 · 64 days ago
- Recorded sightings
- 113
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
We are seeking an experienced MLOps Lead Engineer to take full ownership of our enterprise Machine Learning operations on the Databricks Lakehouse platform. In this role, you will design, automate, and govern end-to-end ML production lifecycles—spanning continuous integration and deployment (CI/CD/CT), central governance, and real-time observability. You will act as the principal technical authority, bridging platform engineering with client-side operations by leading upskilling initiatives for onsite engineering teams.
Requirements
Required Qualifications & Experience
- Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations.
- Core Technical Stack: Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python.
- Automation & DevOps: Strong experience building automated CI/CD/CT pipelines using Databricks Asset Bundles (DABs), Azure DevOps, or GitHub Actions.
- Governance & Security: Deep understanding of enterprise security controls, secret management (Key Vault/KMS), and multi-environment deployment isolation.
- Stakeholder Management: Proven track record in a client-facing technical lead role, with strong communication skills to drive enablement, workshops, and technical handovers.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Source details
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- Pay
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- Location & working pattern
St. Louis, Missouri, United States
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- Work authorization
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