Machine Learning Engineer – AI Personalization, Recommendation Systems, Agentic AI, Google-Backed, 400M+ Downloads
- 50K-60K
- Bengaluru, On-site
Full Job Description
About the Company
Pioneering AI-Powered Consumer Technology | Redefining Digital Experiences
A cutting-edge consumer technology innovator backed by industry giants Google and Jio Platforms, revolutionizing how millions engage with personalized content through AI-driven lock screen experiences and live entertainment platforms. Building next-generation recommendation engines and agentic AI systems at massive scale, transforming mobile engagement through intelligent personalization.
Job Description – MLE
Seeking a Machine Learning Engineer to design, build, and deploy high-impact recommendation systems and agentic AI solutions. This role blends classical ML, deep learning, and autonomous AI to power personalized user experiences at scale.
What You’ll Do:
Develop, deploy, and maintain large-scale recommendation systems using ML, ranking algorithms, and statistical modeling.
Operate ML pipelines: data prep, model training, evaluation, and deployment across high-volume datasets.
Monitor model performance, detect drifts, and optimize algorithms for improved personalization.
Build agentic AI systems that autonomously optimize ML workflows, tune hyperparameters, and improve ranking policies.
Apply LLMs, embeddings, RAG architectures, and multimodal generative models for semantic understanding and content classification.
Explore reinforcement learning and contextual bandits to power next-gen personalization and automated decision-making.
Collaborate closely with engineering, data, and product teams to implement intelligent, scalable solutions.
Required Skills & Experience:
2.5–5.5 years in Machine Learning, with hands-on experience in recommendation models.
Strong Python programming, ML libraries, and statistical modeling expertise.
Experience with LLMs, embeddings, RAG systems, and generative AI.
Knowledge of reinforcement learning, contextual bandits, or self-improving systems.
Familiarity with deploying ML models in production environments.
Excellent problem-solving, analytical, and collaborative skills.
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