[Remote] Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Calendly is a rapidly growing company that provides scheduling solutions relied upon by millions. They are seeking a Machine Learning Engineer to execute the full machine learning lifecycle, from problem discovery through model deployment and monitoring, to enhance customer experiences.

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 and documenting what you learn for the team
• Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly
• Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward
• Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines
• Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team’s on-call rotation and incident response
• Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies
• Be a frequent user of AI Tools and champion of adoption to the rest of the company

Skills

• 4+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production
• Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining
• Experience developing and implementing statistical and ML models to uncover patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing
• Hands-on experience implementing ML models using a managed service (for example, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that produced tangible impact for end users
• Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases
• Strong programming (Python / Scala / Java / SQL etc) and data engineering skills
• Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI
• Experience working with time series data and related machine learning problems. Working knowledge of semantic search and embeddings
• Recognize when to seek assistance and willing to learn whatever is needed to get the job done; curiosity and growth mindset are essential
• You have strong verbal and written communication skills. Ability to communicate complex technical concepts to both technical and business stakeholders. 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

Benefits

• Top Performer Bonus program (or Sales incentive)
• Equity awards
• Competitive benefits
• Occasional travel for company events, team collaboration, or offsites

Company Overview