Senior Machine Learning Engineer, Shopping AI

Zillow Zillow · Consumer · United States · Remote

Senior Machine Learning Engineer focused on building and shipping production ML models for Zillow's core user experience, including ranking, recommendations, search, and autocomplete. The role involves owning the full model lifecycle, from experimentation to deployment and monitoring, and pioneering the application of deep learning and LLMs to enhance the home shopping experience. Collaboration with cross-functional teams and contribution to ML infrastructure are key aspects.

What you'd actually do

  1. Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications.
  2. Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces.
  3. Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring.
  4. Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience.
  5. Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time.

Skills

Required

  • 3-5 years of experience in developing applications in search, personalized ranking, or recommender systems
  • Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
  • Strong programming skills in a high-level language such as Python or Java
  • Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
  • Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
  • Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring.

Nice to have

  • A Master's degree + 3 yrs or BS with a minimum of 5 yrs of experience (preferably in large consumer tech companies)
  • Prior experience or high level of curiosity with generative AI and excitement to collaborate on what they’ve learned!

What the JD emphasized

  • developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
  • Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring.

Other signals

  • production machine learning systems
  • personalized ranking & recommendations
  • semantic search
  • generative AI
  • LLMs