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Tier-1 firm, mid-level role in Bangalore; specialized GenAI stack reduces generalist competition.
Highly specialized GenAI and ML engineering skills limit cross-industry transferability.
Explicit 4–7 years requirement plus mandatory GenAI, PyTorch, cloud, and MLOps skills.
Design, build, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Fine-tune foundation models with domain-specific data and optimize prompt engineering for accurate outputs.
Collaborate with data engineers and MLOps teams to productionize AI models on cloud platforms (Azure, AWS, GCP) ensuring scalability, robustness, and compliance.
4 to 7 years of experience in Generative AI and related technologies.
Bachelor’s degree in Technology (B.E/B.Tech), M.Tech, or MCA.
Proficiency in Python, PyTorch, Hugging Face Transformers, and cloud platforms Azure/AWS/GCP.
Experience with orchestration frameworks (LangChain/Langgraph), REST APIs (FastAPI/Flask), ML pipeline tools (MLflow/Weights & Biases), and CI/CD pipelines for ML deployments.
Experienced in productionizing Generative AI solutions with strong expertise in large language models and orchestration frameworks.
Skilled at integrating AI models into enterprise-level applications and managing ML workflows across cloud environments.
Comfortable with iterative performance evaluation, prompt optimization, and staying current with latest GenAI research and tools.