Machine Learning Engineer

Lumenalta; United States; Remote; PHP 6,293,000 - 9,440,000; Full time

Job summary

Lumenalta is seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. You’ll bridge data engineering and ML, building infrastructure and workflows that move models from experimentation to production deployments.

Ideal candidates have 3-5+ years in MLOps, hands-on MLflow, and experience with feature stores and scalable deployment patterns. This fully remote role supports LATAM with core-time overlap to align with Pacific/Central/Eastern U.S.

Qualifications

• 3-5+ years in MLOps or DevOps for ML with production deployments.
• Hands-on MLflow experience in Databricks or standalone environments.
• Experience building feature stores (Databricks Feature Store or equivalent).
• Experience deploying ML models at scale with real-time and batch inference.

Responsibilities

• Design and maintain MLflow workflows for experiment tracking and registry.
• Build Feature Store infrastructure for reusable feature pipelines.
• Develop model deployment pipelines with serving, A/B testing, versioning, rollback.
• Implement CI/CD pipelines for ML with automated testing and validation gates.
• Orchestrate distributed model training on Databricks for efficiency and reproducibility.
• Monitor models for drift and performance, triggering retraining.
• Collaborate with data scientists and data engineers to reduce friction between prod and dev.

Skills

MLflow

Databricks

Feature Store

CI/CD for ML

Model monitoring

MLOps

Tools

Databricks

CI/CD tooling

Monitoring tooling

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.

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

Application Deadline

Applications will be accepted until September 20th, 2026. Candidates can expect feedback by September 28th, 2026.