Machine Learning Engineer

Calendly's Data Science & Machine Learning team drives business insights, strategic decision making, and customer experiences through impactful innovation. The team works closely with product, design, marketing, customer success, and engineering to implement ML models that improve the customer journey.

• Own ML-powered features end-to-end from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.
• Understand and share domain knowledge, documenting learnings for the team.
• Prioritize work independently, balancing feature development, quality, and maintenance.
• Collaborate with teammates through pairing, reviewing, and knowledge sharing.
• 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, participate in on-call rotation and incident response.
• Serve as subject matter expert for owned features and services, including data contracts, SLAs, and dependencies.
• Be a frequent user of AI tools and champion their adoption across the company.

• 4+ years of industry experience in applied Machine Learning or closely related fields, with a track record of shipping and operating ML models in production.
• Demonstrated ability to traverse the full ML lifecycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, training, validation, serving, monitoring, and retraining.
• Experience developing statistical and ML models for revenue forecasting, churn analysis, personalization, recommendation, anomaly detection, or natural language processing.
• Hands-on experience implementing ML models using managed services like Vertex AI or SageMaker for high-traffic, low-latency, large-data applications.
• Understanding of foundation models and the open-source ecosystem, including fine-tuning and prompt engineering.
• Strong programming skills in Python, Scala, Java, SQL, and data engineering.
• Proficiency in ML frameworks such as Keras, TensorFlow, PyTorch, and ETL/ML workflow frameworks like Apache Spark, Beam, Airflow, and Vertex AI.
• Experience with time series data and related ML problems.
• Working knowledge of semantic search and embeddings.
• Strong verbal and written communication skills; ability to communicate complex technical concepts to technical and business stakeholders.
• Comfortable working remotely with tools like Slack and Confluence.
• Authorized to work lawfully in the United States; Calendly does not engage in immigration sponsorship at this time.

Base salary ranges by tier: Tier 1: $202,542—$245,434; Tier 2: $185,664—$224,981; Tier 3: $168,785—$204,528 USD. All full-time (30 hours/week) employees are eligible for equity awards and competitive benefits. This role may require occasional travel for company events, team collaboration, or offsites.

Apply via the Greenhouse job posting. For accommodations, contact recruiting@calendly.com.