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Popular ML role, mid-level experience, metro location, and broad technical requirements create high competition.
Core ML skills are transferable, but LLM, big-data and product experience increase domain specificity to medium.
Explicit 4–6 years and many mandatory ML, LLM, big-data, and container skills produce high shortlisting strictness.
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Lead end-to-end design, development, and deployment of AI/ML solutions including Large Language Models across product lines.
Own AI/ML modules from data processing through model development, testing, and production deployment.
Provide technical leadership and ensure adherence to best practices for a team of data scientists.
4-6 years experience in Data Science and AI/ML product development with leadership responsibilities.
Proficiency in Python and ML frameworks such as TensorFlow, Keras, or PyTorch.
Strong knowledge of ML algorithms, Deep Learning, NLP, Anomaly Detection, and model lifecycle management.
Experience with SQL, NoSQL, ElasticSearch, Big Data tools (Spark, Kafka), and container/orchestration technologies (Docker, Kubernetes).
Experienced in managing AI/ML projects in agile, fast-paced environments with multiple concurrent priorities.
Skilled in applied research and capability building around cutting-edge ML, Deep Learning, and AI technologies including LLMs.
Demonstrated ability to translate business needs into technical solutions and lead cross-functional collaborations.