Machine Learning Engineer

📋 Description

• Own ML features from design to deployment.
• Collaborate to scope work and define success metrics.
• Understand domain knowledge and document learnings for the team.
• Prioritize work independently, balancing feature development and maintenance.
• Troubleshoot deployment pipelines for ML services and data pipelines.
• Use monitoring tools to triage alerts and participate in on-call rotation.

🎯 Requirements

• 4+ years in applied ML with production models.
• End-to-end ML lifecycle: EDA, feature engineering, training, serving, monitoring.
• Models for revenue, churn, personalization, NLP.
• Hands-on with managed services (Vertex AI or SageMaker).
• Strong programming and data engineering: Python/SQL/Java/Scala.
• Proficiency with TensorFlow, PyTorch, Keras; Spark/Beam/Airflow.

🎁 Benefits

• Remote-friendly with global teams.
• Top Performer Bonus program (or Sales incentive).
• Equity awards.
• Competitive benefits package.
• Salary ranges disclosed in the posting.
• Opportunity to learn and grow in ML at Calendly.