IN_Senior Associate_Test Automation_Emerging Businesses_Advisory_Bangalore

Responsibilities:

• Design, build, and deploy generative AI solutions using LLMs such as OpenAI, Anthropic, Mistral, or open-source models (e.g., LLaMA, Falcon).

• Fine-tune and customize foundation models using domain-specific datasets and techniques

• Develop and optimize prompt engineering strategies to drive accurate and context-aware model responses.

• Implement model pipelines using Python and ML frameworks such as PyTorch, Hugging Face Transformers, or LangChain.

• Agentic AI implementation expertise using Crew.ai or Lang chain

• Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP).

• Knowledge on Azure/GCP/AWS AI platform like Azure AI Foundry or GCP Vertex

• Ensure robustness, scalability, and compliance of AI models in deployment environments.

• Good to have experience in finetuning models

• Good to have experience in SLM

• Integrate GenAI into enterprise applications via APIs or custom interfaces.

• Evaluate model performance using quantitative and qualitative metrics, and improve outputs through iterative experimentation.

• Keep up to date with the latest research in GenAI, foundation models, and relevant open-source tools.

Mandatory skill sets:

• Generative AI (LLMs, Transformers)

• Python, PyTorch, Hugging Face Transformers

• Azure/AWS/GCP cloud platforms

• LangChain/Langgraph or similar orchestration frameworks

• REST APIs, FastAPI, Flask

• ML pipeline tools (MLflow, Weights & Biases)

• Git, CI/CD for ML (e.g., Azure ML, SageMaker pipelines)

Preferred skill sets:

• RAG (Retrieval-Augmented Generation)

• Vector DBs (FAISS, Pinecone, Weaviate)

• Streamlit/Gradio for prototyping

• Docker, Kubernetes (for model deployment)

• Data preprocessing & feature engineering

• NLP libraries: spaCy, NLTK, Transformers

Years of experience required:

4 to 7 years

Education qualification:

B.E/B.tech/M.tech/MCA