2 days ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Design, build, fine-tune, and deploy generative AI solutions using LLMs, transformer architectures, and domain-specific datasets.
- Develop prompt engineering strategies and agentic AI implementations using Crew.ai, LangChain, or LangGraph.
- Build model pipelines with Python and ML frameworks, and productionize solutions with data engineering and MLOps teams on Azure, AWS, or GCP.
- Integrate GenAI capabilities into enterprise applications through REST APIs and custom interfaces.
- Evaluate model performance using quantitative and qualitative metrics and improve outputs through iterative experimentation.
- Ensure deployed AI models are robust, scalable, and compliant, while keeping current with GenAI research and open-source tools.
Requirements
- 4 to 7 years of experience is required.
- Bachelor of Technology, B.E., B.Tech., M.Tech., or MCA qualification is required.
- Strong experience with Generative AI, LLMs, transformers, Python, PyTorch, and Hugging Face Transformers.
- Experience with Azure, AWS, or GCP cloud platforms and AI services such as Azure AI Foundry or GCP Vertex.
- Proficiency with LangChain, LangGraph, or similar orchestration frameworks; REST APIs; FastAPI; and Flask.
- Experience with ML pipeline tools such as MLflow and Weights & Biases, plus Git and ML CI/CD platforms such as Azure ML or SageMaker Pipelines.
- Preferred experience includes RAG, FAISS, Pinecone, Weaviate, Streamlit, Gradio, Docker, Kubernetes, data preprocessing, feature engineering, spaCy, and NLTK.
- Preferred experience includes model fine-tuning and small language models.
Benefits
- PwC offers inclusive benefits, flexibility programmes, mentorship, wellbeing support, and professional growth opportunities.
Tech Stack
AWSAzureDockerFastAPIFlaskGitGoogle Cloud PlatformHugging Face TransformersKubernetesMLflowNLTKPythonPyTorchspaCy
Categories
About PwC
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