
Kuku FM
3 weeks ago
About the job
As a Machine Learning Engineer II in Recommendation, you will be instrumental in advancing our recommendation algorithms and content embeddings, directly driving the growth and success of our Video and Audio Stories Platform.
Responsibilities :
- Recommendation Systems: Design and develop large-scale recommendation systems serving millions of users, with a strong focus on personalization, scalability, and efficiency.
- ML Execution: Drive the ML execution, specifically around feed ranking and recall oriented candidate generation systems.
- Technical Ownership: Provide guidance in ML model formulation, experimentation, and deployment.
- Take end-to-end ownership of ML systems, including key user satisfaction metrics.
- Architecture & Strategy: Contribute to the architectural strategy and design of complex ML systems that meet the needs of users, and content stakeholders.
Requirements :
- Model Training & Serving: Hands-on experience training and serving large-scale ML models using frameworks such as PyTorch or TensorFlow.
- Production Experience: Proven track record of productionising machine learning models, including designing and managing end-to-end ML systems and data pipelines.
- Recommendation Expertise: Direct experience in building and applying large-scale (million+ users) machine learning solutions for feed ranking and personalized recommendations.
- Research Awareness: Stay up-to-date with the latest advancements in recommender systems, data engineering, and applied machine learning.
- Education & Experience: Bachelors or Masters in Computer Science, Machine Learning, Statistics, or a related engineering field, with 2-4 years of relevant experience.
(ref:hirist.tech)
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