Description:

Calendly is seeking a Senior Machine Learning Engineer to join their Data Science & Machine Learning team, focusing on innovation in data, analytics, and AI.
The role involves executing the full machine learning lifecycle to deliver business value and drive new initiatives using the latest advancements in ML.
The engineer will collaborate with cross-functional teams to drive business insights and growth, creating exceptional experiences for customers.
Daily responsibilities include working with large-structured time series data sets to build and improve machine learning models for product use cases.
The engineer will collaborate with software engineers, product managers, and data scientists to prioritize requirements for machine learning models.
Responsibilities also include developing, "productionizing," and operating machine learning models and pipelines at scale for both batch and real-time use cases.
The role requires leveraging cloud services and tools to create reusable, high-performing machine learning systems, ensuring fast model development and low-latency serving.
The engineer will optimize ML models to meet latency SLAs and launch live experiments to evaluate model performance.

Requirements:

Candidates must have 5+ years of industry experience in applied Machine Learning, along with an MS or PhD in relevant fields.
A deep understanding of the full spectrum of the ML lifecycle is required, including EDA, feature engineering, data visualization, and model training and validation.
Experience in developing and implementing advanced statistical and ML models for various applications such as revenue forecasting and anomaly detection is necessary.
A consistent record of implementing ML models using managed services like VertexAI or Sagemaker for high traffic, low latency applications is essential.
Candidates should have a deep understanding of foundation models, open source ecosystems, and model fine-tuning.
Strong programming skills in Python, Scala, Java, and SQL are required, along with proficiency in ML frameworks such as Keras, Tensorflow, and PyTorch.
Experience with time series data and related machine learning problems is necessary, as well as familiarity with Retrieval-Augmented Generation techniques.
Candidates should possess strong verbal and written communication skills to convey complex technical concepts to both technical and business stakeholders.
The ability to work remotely and use enabling tools like Slack and Confluence is required.
Candidates must be authorized to work lawfully in the United States, as Calendly does not engage in immigration sponsorship.

Joining Calendly offers the opportunity to make a significant impact as millions of users rely on their products.
Employees will have the chance to accelerate their careers and work alongside talented individuals.
Full-time employees are eligible for a Quarterly Corporate Bonus program and equity awards.
Competitive benefits are provided, which can be reviewed on Calendly's careers page.
The expected annual base salary ranges from $170,000 to $276,000 depending on the geographic location and tier.