Machine Learning Engineer – Recommendation Systems

Position: Machine Learning Engineer – Recommendation Systems | $ 60K-70K
Location: Bengaluru

Pioneering AI-Powered Consumer Technology | Redefining Digital Experiences

Backed by Google and Jio Platforms. Revolutionizing how 400M+ users engage with personalized content through AI-driven lock screens and live entertainment platforms. Building next-generation recommendation engines and agentic AI systems at massive scale.

What the role demands:

Classical ML & Recommendation Systems

→ Design and deploy large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning

→ Build machine learning models on high-volume, diverse data sources for personalization, prediction, and content understanding

→ Own data preparation, model training, evaluation, and deployment pipelines end-to-end

→ Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities

→ Develop rapid experimentation workflows that validate hypotheses and measure real-world business impact

Agentic Systems & Next-Gen AI

→ Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, and orchestrate ML workflows with minimal human intervention

→ Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling

→ Design intelligent agents that automate repetitive decision-making-candidate generation tuning, feature selection, context-aware content curation

→ Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization

This role operates at the intersection of classical ML craftsmanship and forward-looking agentic AI innovation.