IN-Senior Associate_AI Engineer_Data Analytics_Advisory_Bangalore at pwc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

01 Aug, 26

Salary

0.0

Posted On

03 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, LLM frameworks, Prompt engineering, Spark, Microservices, Kubernetes, Terraform, CI/CD pipelines, FastAPI, Vector databases, MLOps, AWS, GCP, RAG systems, Machine learning, Data analytics

Industry

Professional Services

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. 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. 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. Job Position Title: Senior Associate_AI Engineer_Data Analytics_Advisory_Bangalore Responsibilities: Description: 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 data scientists and product managers, to acquire, process, and manage data for AI/ML model integration and optimization. • Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI/ML models. • Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements. • Familiarity with tools like Terraform, CloudFormation, and Pulumi for efficient infrastructure management. • Create and manage CI/CD pipelines using Git-based platforms (e.g., GitHub Actions, Jenkins) to ensure streamlined development workflows. • Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments. • Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment. • Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development. • Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC. • Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs. • Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling. • Design and execute rigorous A/B tests for machine learning models, analyzing results to drive strategic improvements and decisions. • Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function. • Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and deployment. Enable Skills-Based Hiring No Primary Skill Set GenAI / LLM Engineers (Python, FastAPI, Microservices, K8s, RAG, VectorDBs) Mandatory skill sets: GenAI / LLM Engineers (Python, FastAPI, Microservices, K8s, RAG, VectorDBs) Preferred skill sets: ML, AWS or GCP Years of experience required: 4-6yrs Education qualification: B.Tech / M.Tech / M.E / MCA/B.E Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Amazon Web Services (AWS) Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 25 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date May 17, 2026 Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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Responsibilities

You will design and implement scalable data pipelines and AI/ML models while optimizing LLM inference architectures for enterprise-grade solutions. Additionally, you will collaborate with cross-functional teams to manage data integration and ensure high-quality performance through rigorous testing and MLOps practices.