Machine Learning Engineer

Lumenalta; United States; Remote; CAD 110,000 - 192,000; Full time

Benefits offered by this job

Flexible working hours in a remote env

Health insurance (medical and dental)

Professional development fund

15 days paid time off annually

Soft-skill development courses

Job summary

Lumenalta is hiring an experienced MLOps Engineer to operationalize ML at scale on the Databricks platform. You will bridge data engineering and ML, building infrastructure and workflows to move models from experimentation to production deployments.

You will design MLflow-based workflows, build Feature Store pipelines, and implement CI/CD for ML. Expect collaboration with data scientists and engineers in a fully remote role across North America.

Qualifications

• 3-5+ years in MLOps, ML platform engineering, or DevOps for ML.
• Hands-on with MLflow for tracking, registry, and projects.
• Experience building/consuming Feature Store solutions.
• Proven experience deploying and serving ML models at scale.
• Automated pipelines for training, validation and deployment using CI/CD.
• Strong Databricks experience for distributed training and orchestration.
• Knowledge of drift monitoring, alerting, and retraining triggers.

Responsibilities

• Design and maintain MLflow-based workflows for experiment tracking and registry.
• Build Feature Store infrastructure for reusable feature pipelines.
• Develop model deployment pipelines with serving infra and rollback strategies.
• Implement ML-focused CI/CD pipelines with automated testing and gates.
• Orchestrate distributed model training on Databricks for efficiency and reproducibility.
• Monitor deployed models for drift and performance; trigger retraining when needed.
• Collaborate with data scientists and engineers to reduce friction between environments.

Tools

MLflow

Databricks

Feature Store

CI/CD for ML

Model deployment

Monitoring

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.

Salary range: CA$110,000 - CA$192,000 annually, with final compensation determined by your qualifications, expertise, experience, and the role's scope.

Location:

This is a fully remote position; however, candidates must be based in regions that align with the Pacific, Central, or Eastern U.S. time zones to ensure effective collaboration with client and team schedules.

In addition to competitive pay, we offer a variety of benefits to support your professional and personal growth, including:

• 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.

This is a full-time position requiring a minimum of 40 hours per week, Monday through Friday.

Application Deadline

Applications will be accepted until November 8th, 2026. Candidates can expect feedback by November 16th, 2026.