Data Scientist (AI/ML)

About the job

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. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. • 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. Responsibilities: • 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. Required Skills: • At least 4+ years of total & relevant experience in AI/ML or a related field. • 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. Preferred Qualifications: • prior experience in industries leveraging AI/ML technologies would be advantageous.

Requirements

• Python
• ML frameworks
• Cloud Services
• MLOps

Qualifications

• B.Tech
• M.Tech
• MCA
• MBA

Preferred Technologies

• Python
• ML frameworks
• Cloud Services
• MLOps