Lead Machine Learning Engineer
Tasks
- Apply exploration exploitation strategies
- Architect unified re engagement approach
- Build onboarding and recommendation models for cold start
- Define success metrics and production SLOs
- Design high commitment ranking engine
- Develop multi stage hybrid retrieval pipelines
- Implement semantic vector search
- Lead machine learning strategy for onboarding and re engagement
- Mentor engineers and lead ML projects from research to production
- Optimize entry surfaces start rate and time to play
- Run A B testing and online experimentation
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | Airflow | Apache Beam | Apache Spark | B testing | Bandits | Causal Inference | DevOps | Distributed Systems | Docker | Exploration/exploitation | Google BigQuery | Hybrid retrieval | JAX | Kubernetes | Learning-to-Rank | Low Latency | Low-Latency Systems | MLOps | MLflow | Machine Learning | Neural Networks | Online Experimentation | Online Serving | PyTorch | Python | Ranking | Ray | Recommendation Systems | Reinforcement Learning | Retrieval | Scalable architectures | Semantic Search | Service Level | Service-Level Objectives | TensorFlow | Vector Search | Weights and Biases
Education
N/A
Regions
Countries
States
Cities
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