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Mid-level GenAI role in Bangalore with common 3-4 year requirement increases applicant competition.
Core ML and LLM skills are transferable, but voice AI and telecom platform specifics increase domain sensitivity.
Explicit 3–4 year requirement plus mandatory LLM, MLOps, and programming skills make filters strict.
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Design, build, and productionize scalable AI systems across Generative AI, AI platforms, AI gateways, Voice AI, LLM fine-tuning, ML training, and ML pipelines.
Own end-to-end AI initiatives including problem understanding, architecture, experimentation, model and pipeline development, deployment, observability, and continuous improvement.
Develop production-ready GenAI applications, AI platform capabilities, Voice AI systems, ML pipelines, and handle LLM fine-tuning and training workflows.
3 to 4 years of hands-on experience in AI/ML, GenAI, or ML engineering.
Strong programming skills in C, C++, and Python.
Experience in GenAI/LLM application development, ML training and evaluation workflows, and ML/LLM frameworks.
Knowledge of containerization (Docker), workflow orchestration tools (Airflow, Prefect, Kubeflow, Dagster, or similar), and scalable system design.
Experienced in building and deploying practical AI/ML systems with end-to-end ownership of production readiness and observability.
Comfortable working across application engineering, ML engineering, LLM systems, APIs, infrastructure, and AI platform components.
Skilled at integrating and fine-tuning LLMs using frameworks such as PEFT, LoRA, and orchestrating ML pipelines in production environments.