Senior Machine Learning Engineer

Summary

Join Calendly's Data Science & Machine Learning team as a Senior Machine Learning Engineer and contribute to impactful machine learning solutions. You will collaborate with cross-functional teams, develop and deploy ML models at scale, and optimize models for performance. This role requires 5+ years of experience in applied machine learning or 3+ years with a PhD, a strong foundation in machine learning and statistics, and solid software engineering skills. You will leverage cloud-based ML services and work with various ML tools. Calendly offers a competitive salary, quarterly bonuses, equity awards, and benefits.

Requirements

• 5+ years of industry experience in applied Machine Learning (or 3+ years with a PhD in a relevant field)
• A solid foundation in machine learning and statistics – Extensive experiences with probabilistic modeling, statistical inference, hypothesis testing, and traditional ML techniques; familiarity with recent advancements in large language models and related technologies
• Solid software engineering skills – Proficiency in Python and familiarity with CI/CD for ML, containerization (Docker, Kubernetes), and model observability
• Backend engineering and ML infrastructure – Experience building scalable ML pipelines, integrating ML models into production, and working with cloud platforms (AWS, GCP, Azure); experience with distributed computing or database technologies is a plus
• Familiarity with modern ML tools – Familiarity with PyTorch, TensorFlow, JAX, Hugging Face, LangChain, vector databases, and model-serving frameworks
• The ability to take initiative, solve problems efficiently, and know when to seek help
• Ability to thrive in ambiguity, move fast, and focus on delivering impact
• Ability to clearly articulate technical concepts and work cross-functionally with engineers, product managers, and analysts
• Curiosity and continuous learning – You stay updated on ML/AI advancements and explore opportunities to apply them effectively
• Comfort with working remotely and with enabling tools like Slack, Confluence, etc
• Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time

Responsibilities

• Collaborate cross-functionally with software engineers, product managers, and data scientists to understand business needs, define priorities, and contribute to impactful machine learning solutions
• Develop and deploy ML models and pipelines at scale, supporting both batch and real-time use cases
• Leverage cloud-based ML services and tools to build efficient, reusable, and high-performing machine learning systems that enable rapid model development and reliable serving
• Optimize ML models for performance and scalability, ensuring they meet latency SLAs while handling production traffic; conduct live experiments to evaluate and improve model performance

Benefits

• Quarterly Corporate Bonus program (or Sales incentive)
• Equity awards
• Competitive benefits