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Tier-1 brand, mid-level (3+ yrs), metro Bangalore, and hot GenAI skills amplify competition.
Core LLM and ML engineering skills are transferable, though advisory/client experience adds preference.
Multiple mandatory GenAI, ML, LLMOps and DevOps skills plus 3+ years make shortlisting strict.
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Design and manage ML pipelines including experiment, model, and feature management plus model retraining.
Develop and deploy large language models (LLMs) with expertise in distributed training, GPU architectures, and serving at scale.
Implement DevOps and LLMOps with container orchestration (Kubernetes, Docker) and LLM orchestration frameworks to optimize model fine-tuning and inference.
3+ years of relevant experience in Generative AI, LLM, and related ML technologies.
Bachelor of Engineering or Master of Engineering degree mandatory; MBA/MCA acceptable as per JD but priority on engineering degrees.
Proficient in Python, PyTorch/TensorFlow/Keras, Huggingface, Langchain, Langgraph, Docker, Kubernetes.
Work Experience Required: 3+ years; Notice period: Not explicitly mentioned in the JD.
Hands-on experience with MLflow, SageMaker, Vertex AI, Azure AI, and large language model frameworks (DeepSpeed, vLLM).
Strong skills in DevOps practices, container orchestration, and orchestration frameworks for LLMs.
Experienced in cloud platforms AWS, Azure, GCP and working knowledge of databases like DynamoDB, MongoDB, RDS, Google BigQuery.