Staff Machine Learning Engineer (MLOps) - Remote

Overview

As our first Machine Learning Engineer focusing on MLOps, you will play a pivotal role in operationalizing our ML models, ensuring they are scalable, reliable, and easy to monitor.

In Short

• Design and implement scalable MLOps infrastructure.
• Build and maintain feature stores for ML models.
• Automate ML workflows with CI/CD pipelines.
• Implement resource management and orchestration.
• Monitor and debug production ML systems.
• Collaborate with data scientists and server engineers.
• 3+ years of experience in MLOps or ML Engineering.
• Strong expertise in cloud platforms like AWS or Azure.
• Experience with CI/CD tools such as GitHub Actions or Jenkins.
• Familiarity with orchestration frameworks like Airflow or Kubeflow.

Requirements

• 3+ years of experience in MLOps, ML Engineering, or DevOps for machine learning.
• Experience with machine learning algorithms and model development.
• Strong expertise in cloud platforms (AWS or Azure) for ML deployment.
• Experience with CI/CD pipelines (e.g., GitHub Actions, Jenkins) for ML.
• Strong knowledge of model monitoring tools (e.g., Evidently AI, MLflow).
• Hands-on experience with orchestration frameworks (e.g., Airflow, Kubeflow).
• Familiarity with Pyspark and Databricks is a plus.
• Familiarity with infrastructure-as-code (Terraform, CloudFormation) is a plus.

Benefits

• Competitive salary.
• Generous equity package.
• Full healthcare benefits.
• Technology expense reimbursement.
• Virtual first environment.