Senior Associate

PwC Service Delivery Center

4 - 7 years

14 - 18 Lacs

bengaluru

Posted:1 week ago| Platform:

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Skills Required

mining process automation gcp analytical process improvement configuration management monitoring analytics sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Take a leadership role in designing, developing, and deploying advanced ML and GenAI models (including LLMs, transformers, diffusion models, embeddings) for highimpact realworld applications.
Drive the finetuning and optimization of pretrained foundation models utilizing advanced techniques such as LoRA, prompt engineering, RAG, and transfer learning.
Oversee the construction and integration of innovative retrievalaugmented generation (RAG) pipelines with sophisticated vector databases like Pinecone, Weaviate, PostgreSQL + pgvector, FAISS.
Lead the implementation of scalable MLOps practices for data preprocessing, feature engineering, and model training pipelines.
Strategically collaborate with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) for deployment, scaling, and maintece of complex models.
Act as a liaison between product and engineering teams, embedding and guiding AI capabilities strategic application into various software solutions.
Stay abreast of cuttingedge research and evolving trends in GenAI, NLP, multimodal AI, and applied ML, bringing innovative solutions and insights to the team.
Core Technical Skills (MustHave)
Proficiency in programming with a strong grasp of Python and frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
Extensive handson experience with LLMs, embeddings, text generation, summarization, semantic search, and finetuning.
Indepth understanding and proven experience with SQL/NoSQL databases, data pipelines, feature stores, and ETL processes for ML workloads.
Skilled with vector databases (FAISS, Pinecone, Weaviate, ChromaDB, and pgvector) and their strategic deployment in complex projects.
Advanced knowledge of MLOps tools MLflow, Docker, CI/CD for ML models, model monitoring, ensuring robust lifecycle management.
Expertise in Cloud platforms AWS (SageMaker, Bedrock), GCP (Vertex AI), or Azure (OpenAI), leveraging them for efficient and scalable AIML solutions.
Competency in APIs & Integration REST, gRPC, FastAPI, Flask, with capability to wrap and serve models as sophisticated APIs.

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