MLOps Engineer – Hourly and Full time

This is a fully remote position, open to applicants in Washington.

📋 Description

• Develop and sustain comprehensive ML pipelines from the point of data ingestion through to model deployment.

• Manage model registries, feature stores, and experiment tracking tools (MLflow, W&B).

• Create scalable infrastructure for model serving utilizing Kubernetes and cloud platforms.

• Establish CI/CD workflows for ML models, incorporating testing and rollback strategies.

• Oversee production models, including drift detection, alerting mechanisms, and retraining pipelines.

• Work in conjunction with data scientists and platform engineers to accelerate the delivery of ML solutions.

⛳️ Requirements

• Minimum of 5 years of experience in data engineering, including pipelines, data warehouses, and orchestration.

• At least 2 years of practical experience in ML engineering / MLOps within production settings.

• Proficient in Python, with experience in Airflow, Spark, or comparable orchestration tools.

• Strong understanding of Kubernetes, Docker, and at least one major cloud platform (AWS, GCP, or Azure).

• Familiarity with ML tools such as MLflow, W&B, DVC, or equivalent.

• Must be available full-time (80 hours/week), aligned with EST, and eligible for contracting in Canada (CAD).

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and career advancement.

• Flexible work hours and a supportive remote work environment.