IN_Senior Associate_AI Engineer_Data and Analytics_Advisory_Bangalore
PwC IndiaMatch Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessStrong PwC brand, mid-level (5-8 yrs), Bangalore metro, and broad ML/LLM requirements drive high applicant competition.
LLM and ML engineering skills transfer across industries but require specialized frameworks, yielding medium sensitivity.
Multiple mandatory specialized LLM, ML, and DevOps skills plus explicit 5-8 years requirement make filters stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Design and manage ML pipelines including experiment, model, feature management, and retraining with tools like MLflow, SageMaker, Vertex AI, and Azure AI.
Deploy and optimize large language models (LLMs) leveraging GPU architectures and distributed training using frameworks such as DeepSpeed and vLLM.
Implement DevOps and LLMOps practices for container orchestration using Kubernetes and Docker and orchestrate LLM frameworks like Flowise, Langflow, and Langgraph.
Minimum Requirements
5-8 years of relevant work experience in AI/ML engineering or related roles.
Bachelor of Technology (B.Tech) degree mandatory; MCA, BCA, or M.Tech are acceptable alternatives.
Mandatory skills: Gen AI, LLM, Huggingface, Python, PyTorch/TensorFlow/Keras, Langchain, Langgraph, Docker, Kubernetes.
Work environment primarily focused on cloud platforms AWS, Azure, or GCP; expertise with MLflow and container orchestration is required.
Ideal Candidate Profile
Experienced in end-to-end ML pipeline design and deployment specifically for large language models and generative AI.
Skilled in optimizing model performance with resource-efficient fine-tuning and latency improvements on distributed GPU setups.
Comfortable operating in cloud-native DevOps environments and adept with LLM orchestration frameworks to drive scalable AI solutions.