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Tech Stack
Tools & technologiesGoogle Cloud PlatformPythonPyTorchSQLTensorflow
About the role
Key responsibilities & impact- Design and deploy ML components for channel ranking and guide personalization
- Work with linear scheduling data to create features for program relevance
- Use Qdrant to group similar channels
- Train and iterate on models using TensorFlow/PyTorch
- Own delivery of defined tasks from data exploration to production deployment
Requirements
What you’ll need- 3+ years in MLE
- proficiency in Python/SQL
- experience with TensorFlow/PyTorch
- experience with GCP
- knowledge with FAST or Broadcast TV data structures (preferred)
- experience with Qdrant or similar vector databases (preferred)
Benefits
Comp & perks- medical
- dental
- vision
- 401(k) plan
- life insurance coverage
- disability benefits
- tuition assistance program
- PTO
- bonus eligible
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learning engineeringPythonSQLTensorFlowPyTorchGCPQdrantdata explorationproduction deploymentfeature engineering
