Machine Learning Engineer

Responsibilities

• Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics
• Understand and share domain knowledge, answering domain specific questions for your product area
• Prioritize work independently, balancing feature development, quality, and maintenance
• Troubleshoot deployment pipelines, including build, test, and release steps for ML services and data pipelines
• Use monitoring and observability tools to triage alerts and incidents
• Serve as a subject matter expert for owned features, data contracts, SLAs, and dependencies
• Champion the adoption of AI tools across the company

Requirements

• 4+ years of industry experience in applied Machine Learning or closely related fields
• Demonstrated track record of shipping and operating ML models in production
• Deep ability to traverse the full ML life cycle: EDA, feature engineering, model training, validation, serving, and monitoring
• Experience implementing ML models using managed services like Vertex AI or SageMaker
• Understanding of foundation models, fine-tuning, and prompt engineering
• Strong programming skills in Python, Scala, Java, or SQL
• Proficiency in ML frameworks such as Keras, TensorFlow, or PyTorch
• Experience with ETL and ML workflow frameworks like Apache Spark, Beam, Airflow, or VertexAI
• Experience with time series data, semantic search, and embeddings
• Authorized to work lawfully in the United States

About the Company

Calendly makes things possible for customers through innovation in data, analytics, and AI, helping millions of people manage their schedules and grow their businesses.