machine learning engineer in MLOps

Lumenalta partners with forward-thinking organizations to build scalable technology solutions that improve user experiences and accelerate business growth. Its global teams emphasize transparency, autonomy, technical excellence, and measurable impact.

• Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management;
• Build and manage Feature Store infrastructure for reusable and consistent feature pipelines;
• Develop model deployment pipelines with serving infrastructure, A/B testing support, versioning, and rollback strategies;
• Implement CI/CD pipelines for ML workflows, including automated testing, validation gates, and deployment triggers;
• Orchestrate distributed model training on Databricks while optimizing 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 and production.

• 3–5+ Years of experience 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 in Databricks or standalone environments;
• Experience building and consuming Feature Store solutions, including Databricks Feature Store or equivalent;
• Proven experience deploying and serving ML models at scale using real-time and batch inference patterns;
• Ability to design automated pipelines for model training, validation, and deployment with 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.

• 100% Dedicated to one project at a time;
• Work with a team of talented and friendly senior-level developers;
• Projects provide opportunities to use leading technology;
• Fully remote position open to candidates based in Europe and Africa;
• Candidates must maintain at least a 6-hour overlap with project core business hours, primarily aligned with Central or Eastern U.S. time zones;
• Applications accepted until October 4th, 2026; feedback expected by October 12th, 2026.