机器学习工程师

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.

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.

Flexible working hours in a remote environment.
Health insurance (medical and dental) for T4 Employees.
A professional development fund to enhance your skills and knowledge.
15 days of paid time off annually.
Access to soft-skill development courses to further your career.

Lumenalta partners 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.

Applications will be accepted until July 12, 2026. Candidates can expect feedback by August 1, 2026.