Machine Learning Engineer Job in Bangalore at Kuku FM

Kuku FM is hiring for the role of Machine Learning Engineer!

Responsibilities of the Candidate:

• Algorithm Development: Design, develop, and optimize deep learning models for content understanding, candidate retrieval, ranking, and recommendation algorithms to enhance audio content discovery and engagement on our platform.
• Data Analysis: Analyse user behaviour data, audio metadata, and other relevant datasets to identify patterns, trends, and insights that inform algorithmic improvements.
• Model Training and Evaluation: Train, fine-tune, and validate deep learning models using large-scale datasets. Implement rigorous evaluation methodologies to measure the performance and effectiveness of recommendation algorithms.
• Candidate Retrieval and Ranking: Develop advanced algorithms for retrieving and ranking potential audio candidates to be recommended to users, ensuring high relevance and diversity in recommendations.
• Feature Engineering: Collaborate with cross-functional teams to identify and engineer relevant features that enhance the accuracy and quality of recommendation algorithms.
• Research and Innovation: Stay up-to-date with the latest advancements in deep learning, recommender systems, and related fields. Apply cutting-edge research to improve the performance of our algorithms.
• Experimentation: Plan and execute A/B tests and controlled experiments to validate algorithmic changes and improvements.
• Collaboration: Work closely with data engineers, software engineers, product managers, and designers to integrate and deploy algorithms into the platform.
• Documentation: Maintain clear and organized documentation of algorithms, experiments, and findings to facilitate knowledge sharing and collaboration within the team.

Requirements: 

• Experience: 1-2 years
• Education: Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or a related field
• Hands-on experience developing and deploying deep learning models, focusing strongly on recommender systems and algorithm development, specifically in ranking
• Solid understanding of machine learning and deep learning concepts, including neural networks, content embeddings, collaborative filtering, and ranking algorithms
• Experience with data preprocessing, feature engineering, and data analysis techniques
• Familiarity with cloud computing platforms (AWS, Google Cloud, etc.) for scalable model training and inferencing
• Technical Skills: Python, PySpark, and relevant deep learning frameworks (PyTorch, TensorFlow, etc.)
• Problem-solving: Strong analytical and problem-solving skills, with the ability to translate data insights into actionable recommendations
• Communication: Excellent communication skills, both written and verbal, to collaborate effectively with cross-functional teams and present complex ideas