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Strong employer brand, metro location, and mid-level experience raise competition despite niche LLM skill needs.
Highly specialized LLM and MLOps skills limit transferability across non-ML industries.
Multiple mandatory GenAI/LLM, PyTorch, Langchain, Kubernetes and explicit 3+ years requirement increases filter strictness.
Design and manage ML pipelines including experiment, model, and feature management.
Develop APIs for scalable model inferencing and fine-tune large language models for optimized performance and resource usage.
Apply DevOps and LLMOps practices using Kubernetes, Docker, and LLM orchestration frameworks like Flowise and Langflow.
Minimum 3 years of experience in Gen AI, LLM, and related technologies.
Mandatory skills: Generative AI, LLM, Huggingface, Python, PyTorch/TensorFlow/Keras, Langchain, Langgraph, Docker, Kubernetes.
Educational qualification: Bachelor or Master of Engineering (BE/B.Tech/Master of Engineering) or MBA/MCA.
Work Experience Required: 3+ years.
Strong experience with cloud platforms (AWS, Azure, GCP) and ML platforms like SageMaker, Vertex AI.
Proven ability to work with distributed training, GPU architectures, and LLM serving frameworks.
Familiarity with data storage technologies (e.g., MongoDB, DynamoDB, RDS) and DevOps monitoring tools (Prometheus, Grafana).