Back
Strong PwC brand, Bangalore location, and mid-level (3+ years) amplify applicant competition.
LLM, ML engineering, and DevOps skills are highly transferable across industries.
Mandatory niche LLM/ML and DevOps stack plus explicit 3+ years requirement increases strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and manage ML pipelines including experiment, model, and feature management, and scalable model inferencing APIs.
Apply expertise in GPU architecture and distributed training/serving of large language models using frameworks like DeepSpeed and vLLM.
Optimize model fine-tuning to improve latency and accuracy while reducing training resources; implement DevOps and LLMOps practices using Kubernetes, Docker, and orchestration frameworks.
Minimum 3 years of experience in Generative AI, LLM development, and related ML pipeline design.
Mandatory skills: Generative AI, LLM, Huggingface, Python, PyTorch/TensorFlow/Keras, Langchain, Langgraph, Docker, Kubernetes.
Education: Bachelor or Master of Engineering (BE/B.Tech/ME/M.Tech) or MBA/MCA.
Work Experience Required: 3+ years; Notice period: Not explicitly mentioned in the JD.
Experienced in large language models deployment and optimization in production environments, with strong GPU and distributed training knowledge.
Proficient in DevOps and LLMOps including container orchestration and model management frameworks within cloud ecosystems (AWS, Azure, GCP).
Strategic problem solver focused on improving model performance and reducing operational resource consumption through practical fine-tuning and automation.