MLOps Engineer (Databricks Platform)

Lumenalta European Economic Area
Remote
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AI Summary

Lumenalta is seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. This role involves building and maintaining ML infrastructure, CI/CD pipelines, and monitoring systems for production ML deployments. Candidates should have 3-5+ years of MLOps experience with hands-on Databricks and MLflow expertise.

Key Highlights
Operationalize machine learning at scale on the Databricks platform.
Design and maintain MLflow-based workflows and Feature Store infrastructure.
Implement CI/CD pipelines for ML workflows and monitor deployed models.
Key Responsibilities
Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management.
Build and manage Feature Store infrastructure to enable reusable, consistent feature pipelines across teams and use cases.
Develop model deployment pipelines, including serving infrastructure, A/B testing support, versioning, and rollback strategies.
Implement CI/CD pipelines tailored for ML workflows, including automated testing, validation gates, and deployment triggers.
Orchestrate distributed model training on Databricks, optimizing for compute efficiency, reproducibility, and cost.
Monitor deployed models for data drift, performance degradation, and system health, triggering automated retraining workflows as needed.
Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation environments and production.
Technical Skills Required
MLflow Feature Store Databricks CI/CD
Benefits & Perks
100% dedicated to one project at a time
Work on projects that allow you to use leading tech
Fully remote

Job Description


At Lumenalta, we partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our global teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact—empowering every team member to do their best work.


We’re seeking an experienced MLOps Engineer responsible for operationalizing machine learning at scale on the Databricks platform. This role bridges data engineering and ML, building the infrastructure and workflows that take models from experimentation to reliable production deployments.


What You'll Be Doing

  • Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management.
  • Build and manage Feature Store infrastructure to enable reusable, consistent feature pipelines across teams and use cases.
  • Develop model deployment pipelines, including serving infrastructure, A/B testing support, versioning, and rollback strategies.
  • Implement CI/CD pipelines tailored for ML workflows, including automated testing, validation gates, and deployment triggers.
  • Orchestrate distributed model training on Databricks, optimizing for compute efficiency, reproducibility, and cost.
  • Monitor deployed models for data drift, performance degradation, and system health, triggering automated retraining workflows as needed.
  • Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation environments and production.


What We're Looking For

  • 3–5+ years in MLOps, ML platform engineering, or DevOps for ML, with proven production ML deployments.
  • Hands-on expertise with MLflow for tracking, registry, and project management within Databricks or standalone environments.
  • Experience building and consuming Feature Store solutions (Databricks Feature Store or equivalent).
  • Proven experience deploying and serving ML models at scale, including real-time and batch inference patterns.
  • Ability to design automated pipelines for model training, validation, and deployment using modern CI/CD tooling.
  • Strong familiarity with Databricks for distributed training, job orchestration, and cluster management.
  • Knowledge of model monitoring practices, including drift detection, alerting, and retraining triggers.


Why Lumenalta is an amazing place to work at

At Lumenalta, you can expect that you will:

  • Be 100% dedicated to one project at a time so that you can innovate and grow.
  • Be a part of a team of talented and friendly senior-level developers.
  • Work on projects that allow you to use leading tech.


Location

This is a fully remote position open to candidates based in Europe and in Africa. While location is flexible, candidates must be willing to maintain at least a 6-hour overlap with core business hours of the project, which are primarily aligned with the Central, or Eastern U.S. time zones to ensure effective collaboration with project teams.


Application Deadline

Applications will be accepted until June 28, 2026. Candidates can expect feedback by July 1, 2026.


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