Staff Machine Learning Engineer

Summary

Join Calendly's Data Science & Machine Learning team as a Staff Machine Learning Engineer and contribute to the development and deployment of machine learning models. You will collaborate with cross-functional teams to define priorities and build impactful solutions. Responsibilities include designing, developing, and deploying ML models at scale, leveraging cloud-based services, and optimizing models for efficiency. The ideal candidate possesses a deep understanding of modern LLMs and Generative AI, strong machine learning and statistical foundations, and solid software engineering fundamentals. The role requires hands-on experience with various ML tools and a collaborative work style. Calendly offers a competitive salary and benefits package.

Requirements

• Deep understanding of modern LLMs and Generative AI – Strong familiarity with recent advancements in large language models, their applications, fine-tuning techniques, retrieval-augmented generation (RAG), multimodal models, and agentic frameworks
• Strong foundation in machine learning and statistics – Proficiency in probabilistic modeling, statistical inference, hypothesis testing, and traditional ML techniques
• Solid software engineering fundamentals – Extensive experience with Python, CI/CD for ML workflows, containerization (Docker, Kubernetes), and monitoring/observability of deployed models
• Backend engineering and ML infrastructure – Proven experience in building scalable APIs, integrating ML models into production systems, and deploying on cloud platforms (AWS, GCP, Azure); familiarity with distributed computing and database technologies is a plus
• Hands-on with modern ML tooling – Practical experience with PyTorch, TensorFlow, Hugging Face, LangChain, vector databases, and model-serving frameworks
• Self-motivated and resourceful – You take initiative, find creative solutions, and don’t let roadblocks stop you from making progress
• Bias for action and results-oriented – You thrive in ambiguity, move fast, and focus on delivering impact rather than just building technology; you recognize when to seek assistance and are willing to learn whatever is needed to get the job done
• Collaborative & communicative – You can work cross-functionally with engineering, product, analytics and business teams to align on goals and deliver solutions that scale
• Curiosity and continuous learning – You stay on top of the latest ML/AI advancements and proactively seek ways to integrate them into real-world applications
• You are comfortable 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 analysts to understand business needs, define priorities, and drive impactful machine learning solutions
• Design, develop, and deploy ML models and pipelines at scale, supporting both batch and real-time use cases; architect ML and backend solutions as needed
• Leverage cloud-based ML services and tools to build reusable, high-performance systems that enable rapid model development, low-latency inference, and seamless model maintenance
• Optimize ML models for scale and efficiency, ensuring they meet latency SLAs while handling Calendly’s production traffic; conduct live experiments to validate and refine model performance

Benefits

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