IN-Senior Associate_AI Engineer_Data & Analytics_Advisory_Bangalore

Job description

**Line of Service** Advisory **Industry/Sector** Not Applicable **Specialism** Data, Analytics & AI **Management Level** Senior Associate **Job Description & Summary** At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. \\*Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " **Job Description & Summary:** A career within….   A career within Data and Analytics services will provide you with the opportunity to help   organisations   uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of   organisational   technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their   organisations   in order to   keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.     **Responsibilities :**         Technical Skills:    • Advanced proficiency in Python.    • Extensive experience with LLM frameworks (Hugging Face Transformers,   LangChain) and prompt engineering techniques  • Experience with big data processing using Spark for large-scale data analytics  • Version control and experiment tracking using Git and   MLflow  • Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.  • DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.  • LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as   vLLM   and   FastAPI, model quantization techniques, and vector database management.  •   MLOps   & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like   TorchServe   or TF Serving, and automated model retraining.  • Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.  • LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security.  • General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow,   PyTorch), and experience with cloud platforms like AWS or GCP.  • Experience in creating LLD for the provided architecture.  • Experience working in microservices based architecture.    Domain Expertise:  • Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation  • Expertise in feature engineering, embedding optimization, and dimensionality reduction  • Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing  • Experience with RAG systems, vector databases, and semantic search implementation  • Proficiency in LLM optimization techniques including quantization and knowledge distillation  • Understanding of   MLOps   practices for model deployment and monitoring  Professional Competencies:  • Strong analytical thinking with ability to solve complex ML challenges  • Excellent communication skills for presenting technical findings to diverse audiences  • Experience translating business requirements into data science solutions  • Project management skills for coordinating ML experiments and deployments  • Strong collaboration abilities for working with cross-functional teams  • Dedication to staying current with latest ML research and best practices  • Ability to mentor and share knowledge with team members    • Develop and maintain microservice architecture and API management solutions using REST and   gRPC   for seamless deployment of AI solutions.  • Collaborate with cross-functional teams, including