Remote MLOps Engineer: Scale ML on Databricks

Lumenalta; United States; Remote; USD 80,000 - 140,000; Full time

Benefits offered by this job

Health insurance

401K Contribution

15 days PTO

Professional development fund

Flexible working hours

Job summary

Lumenalta is seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. This role bridges data engineering and ML, building pipelines and workflows that move models from experimentation to production deployments.

The position requires 3–5+ years in MLOps or DevOps for ML, hands-on MLflow experience, and familiarity with Databricks. You will implement CI/CD for ML and monitor models in production while collaborating with data scientists and

Qualifications

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

Responsibilities

• Design and maintain MLflow-based workflows for experiment tracking, model registry, and lifecycle management.
• Build and manage Feature Store infrastructure for reusable pipelines across teams.
• Develop deployment pipelines with serving infrastructure, A/B testing, versioning, and rollback strategies.
• Implement ML-focused CI/CD pipelines with automated testing and deployment gates.
• Orchestrate distributed model training on Databricks for performance and cost efficiency.
• Monitor deployed models for drift and performance, triggering retraining when needed.
• Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation and production.

Skills

MLOps

CI/CD for ML

Model monitoring

Distributed training experience

Databricks platform

Tools

MLflow

Databricks

Feature Store

Job description

Lumenalta is seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. This role bridges data engineering and ML, building pipelines and workflows that move models from experimentation to production deployments.

The position requires 3–5+ years in MLOps or DevOps for ML, hands-on MLflow experience, and familiarity with Databricks. You will implement CI/CD for ML and monitor models in production while collaborating with data scientists and