Remote Senior Machine Learning Engineer

Summary

Join Calendly's Data Science & Machine Learning team as a Senior Machine Learning Engineer to drive new initiatives using the latest advancements in ML and create magical experiences for customers through innovation.

Requirements

• 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields
• Deep and demonstrated ability to traverse the full spectrum of ML life cycle: EDA, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and re-training
• Develop and implement advanced statistical and ML models to uncover patterns, trends, and predictions (Ex.: revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, natural language processing)
• Consistent record of efficiently implementing ML models using a managed service (VertexAI / Sagemaker) for high traffic, low latency, large data applications that produced substantial impact on the end users
• Deep understanding of the the foundation models, open source ecosystem, model fine-tuning, prompt engineering etc
• Strong programming (Python / Scala / Java / SQL etc) and data engineering skills
• Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch (in that order of importance) and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI
• Deep experience working with time series data and related machine learning problems; working knowledge of semantic search and embeddings
• Familiarity with Retrieval-Augmented Generation techniques to improve content quality, orchestration framework such as Langhcain or Microsoft Semantic kernel
• The ability to recognize when to seek assistance and willing to learn whatever is needed to get the job done; ideally, you have some research experience
• You have strong verbal and written communication skills and the ability to communicate complex technical concepts to both technical and business stakeholders

Responsibilities

• Working with unique, large-structured time series data sets to build and continuously improve innovative machine learning models for Calendly product use cases
• Working collaboratively with partners including software engineering, product managers, decision and data scientists, to impact the business by understanding and prioritizing requirements for machine learning models
• Hands-on developing, "productionizing," and operating machine learning models and pipelines at scale, including both batch and real-time use cases
• Leveraging machine learning cloud services and tools to develop reusable, highly differentiating and high-performing machine learning systems, enable fast model development, low-latency serving and ease of model quality upkeep
• Optimizing ML models to meet latency SLAs at the scale of Calendly's production traffic and launch live experiments to evaluate model performance

Benefits

• Ready to make a serious impact?
• Millions of people already rely on Calendly’s products, and we’re still in the midst of our growth curve — it’s a fantastic time to join us
• Everything you’ll work on here will accelerate your career to the next level
• If you want to learn, grow, and do the best work of your life alongside the best people you’ve ever worked with, then we hope you’ll consider allowing Calendly to be a part of your professional journey