Sr. AIML Engineer

Mandatory Skills: Hands-on experience in building and maintaining Knowledge graphs and Recommendation systems knowledge

Job Title:

Senior AI/ML Engineer - Personalization & Recommendation Systems Role Overview:

Lead the design and deployment of scalable AI/ML solutions focused on real-time personalization recommendation systems and customer knowledge graphs driving measurable improvements in engagement and conversion.

Key Responsibilities

• Design and build collaborative content-based and hybrid recommendation systems
• Develop real-time personalization pipelines and ranking models
• Architect end-to-end ML systems (batch streaming) with low-latency inference
• Build customer knowledge graphs (Neo4j/Neptune) modeling users products and interactions
• Enable Customer 360 insights and context-aware recommendations
• Develop scalable pipelines using Python Spark Kafka Implement feature engineering model training and deployment workflows
• Drive experimentation (A/B testing) and optimize for CTR engagement and conversion Ensure data quality model performance and system reliability
• Apply MLOps practices (CI/CD monitoring model lifecycle management)
• Mentor team members and collaborate with product/business stakeholders

Required Skills Strong

• Python and experience with Pandas PySpark Expertise in recommender systems (matrix factorization deep learning ranking models)
• Experience in entity resolution / record linkage
• Hands-on with graph modeling & graph databases (Neo4j RDF graph embeddings)
• Strong understanding of ML lifecycle experimentation and evaluation metrics (NDCG MAP Precision/Recall)

Nice to Have

• Experience with real-time ML systems and large-scale data (TB/PB)
• Impact Drive personalized customer experiences improve engagement & conversion and enable data-driven decision-making at scale.