Machine Learning Engineer

Calendly Calendly · Enterprise · Remote · Engineering

Machine Learning Engineer at Calendly to deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. Build and operate ML-powered features that create magical experiences for customers. This role is part of a high performing AI team and will be an integral part of building new, machine learning based experiences for internal and external customers.

What you'd actually do

  1. Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.
  2. Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team.
  3. Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly.
  4. Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward.
  5. Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines.

Skills

Required

  • 4+ years of industry experience in applied Machine Learning
  • Python
  • Scala
  • Java
  • SQL
  • Keras
  • Tensorflow
  • PyTorch
  • Apache Spark
  • Apache Beam
  • Apache Airflow
  • VertexAI
  • time series data
  • semantic search
  • embeddings
  • communication skills

Nice to have

  • foundation models
  • model fine-tuning
  • prompt engineering
  • open-source ecosystem

What the JD emphasized

  • shipping and operating ML models in production
  • full spectrum of ML life cycle
  • high-traffic, low-latency, large-data applications

Other signals

  • delivering business value through ML
  • building and operating ML-powered features
  • shipping and operating ML models in production
  • full ML lifecycle