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Mid-level ML role, metro Bengaluru, generalist ML/LLM skills and known brand increase applicant competition.
Core ML, DL and LLM skills transfer across industries, though product-domain knowledge adds moderate bias.
Explicit 4–6 years requirement plus mandatory ML/LLM, DL, big data, and containerization skills.
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Lead design, development, and implementation of AI/ML solutions across product lines including end-to-end AI/ML modules ownership from data processing to deployment.
Provide technical leadership to data science teams ensuring high-quality outputs and best practices adherence.
Conduct research and implement state-of-the-art Machine Learning, Deep Learning, AI, and Large Language Model (LLM)-based solutions with production deployment experience.
4-6 years experience in Data Science and AI/ML product development with proven technical team leadership.
Proficiency in machine learning algorithms, deep learning models, NLP, anomaly detection, and model lifecycle management.
Hands-on experience with Python and ML frameworks (TensorFlow, Keras, PyTorch); strong SQL/NoSQL and ElasticSearch knowledge.
Experience with big data frameworks (Spark, Storm, Databricks, Kafka) and container/orchestration technologies such as Docker, Kubernetes, ECS, or EKS.
Experienced in managing multiple AI/ML projects in fast-paced, agile environments with proven problem-solving and communication skills.
Strong strategic ownership of AI/ML modules and capability to translate business requirements into technical solutions for ML deployment.
Demonstrated expertise with Large Language Models and end-to-end model lifecycle, including optimization and performance tuning.