MLOps Lead Engineer
- Level
- Lead
Not stated in the posting: salary, work type, visa.
Open. First seen 2 October 2026.
About the role
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.
What this role asks for
Particular to this role
Azure DevOps · Delta Lake · GitHub · MLflow · Unity
Rare in Tiger Analytics Inc.'s other 101 open postings.
In most of Tiger Analytics Inc.'s ads
Machine Learning · Python
Named in most of its open postings, whatever the role.
Read against Tiger Analytics Inc.'s other open postings on this site.
The team: MLE HIRES STEADILY
This role is one of 26 open in MLE. 4 were posted in the last 30 days and the oldest in September: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Machine Learning (24 of 26), Python (23 of 26), AWS (17 of 26), Generative AI (17 of 26), LLM (15 of 26), GCP (14 of 26), LangChain (14 of 26)
OTHER ROLES ON THIS TEAM
- UI Path + Azure AI Engineers posted Oct 8
- Forward Deployed Engineer (FDE) - GenAI / Agentic AI posted Oct 5
- Forward Deployed Engineer (FDE) - GenAI / Agentic AI posted Sep 30
- Lead AI Architect & Delivery Manager posted Sep 29
- Forward Deployed AI Engineer -Neo4j / Knowledge Graph posted Sep 1
- Forward Deployed Engineer (Generative AI) posted Aug 25
- Lead AI Engineer posted Aug 4
- Forward Deployed Engineer (Generative AI) posted Jul 14
- AI and Integration Architect posted Jun 19
- Forward Deployed Engineer (Generative AI) posted May 18
- Full Stack Gen AI Engineer posted Feb 11
- Generative AI Leader/Architect posted Jan 26
- GenAI Engineer posted Jan 19
- GenAI Architect posted Jan 19
- Machine Learning Engineer posted Dec 9
- Machine Learning Engineer (with Vertex AI Experience) posted Nov 20
- Senior Agentic AI Engineer posted Oct 28
- Senior AI Engineer posted Aug 5
- Senior Machine Learning Engineer (GCP) posted Aug 1
- Machine Learning Architect posted Jul 3
- Databricks Architect posted Jun 24
- Gen AI Data Engineer posted Apr 14
- ML Ops Architect posted Mar 4
- MLOps Engineer(NJ) posted Oct 26
- Machine Learning Engineer (Canada) posted Sep 12
From the team and dates on Tiger Analytics Inc.'s own job board.
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