USI | Audit Services | AI and Data Science Engineer III

Role overview

USI | Audit Services | AI and Data Science Engineer III at Deloitte

If yes, we have just the role for you.

Responsibilities

• You will be joining our collaborative Data Science team which leverages the most advanced technologies in machine learning and artificial intelligence to achieve the Deloitte Audit and Assurance vision of an AI-enabled audit.
• Collaborate daily with Data Science Managers to solve complex data science problems that emerge within your workstream and others.

Required qualifications

• Deep knowledge in at least one of our core competencies (NLP and generative AI, Anomaly Detection, Time Series, Knowledge Graph)
• Experience with at least one cloud-based ecosystem (Azure, GCP, AWS)

Employment details

• Location: Bengaluru [Karnataka] [India]

Application details

• Apply rigorous data science practices on your specific assigned workstreams through the entire data science development and deployment lifecycle
• Stay up to date with the latest trends, techniques, and advancements in data science and identify opportunities for their application

About the employer

• Effectively explain technical concepts The Team This team leverages the most advanced technologies in machine learning and artificial intelligence to achieve the Deloitte Audit and Assurance vision of an AI-enabled audit.

Additional role details

• AI and Data Science Engineer III Do you have a passion for artificial intelligence, machine learning, and data analysis?
• Do you yearn to have the impact of your work recognized and valued by more than just your development team?
• Some of our current projects focus on generative AI, prompt engineering, LLMs, anomaly detection, clustering, and knowledge graphs.
• As AI and Data Science Engineer, you will focus on supporting the Data Science group and actively participate in the entire lifecycle of a data science project, with a focus on feature engineering, creating models, and boosting their performance and accuracy, as well as guiding and supervising more junior resources.
• Work you will do
• Develop high-quality, production-ready code (readable, well-tested, with well-designed APIs)
• Collaborate with subject matter experts to obtain an understanding of the underlying business problem, and to define and refine the corresponding technical solution.
• Be a key contributor to the planning and direction of a project and effectively prioritize goals and objectives
• Location - Bengaluru Shift Time - 9:00 am to 6:00 pm Qualifications Required:
• 5-6 years of relevant industry experience designing, developing, and deploying machine learning models
• Undergraduate degree in quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
• Solid understanding of machine learning model development life cycles
• Understanding of LLMs and prompt engineering
• Demonstrated ability to write high-quality, production-ready code (readable, well-tested, well-documented, with well-designed APIs)
• Extensive experience with Python and relevant libraries (NumPy, Pandas, Scikit-learn, etc.)
• Experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI and LangChain
• Knowledge of Docker, Jenkins, Kubernetes, and other DevOps tools
• Excellent verbal and written communication skills
• Ability to travel as needed (<25%) Preferred:
• Master’s degree or PhD in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
• Extensive experience with Microsoft Azure, including certification in machine learning
• Experience with machine learning pipelines (Azure ML)
• Experience in an Agile working environment and related project management tools (Jira, Azure DevOps, etc.)
• Proficiency in utilizing prompt engineering techniques to effectively guide the generation process and obtain desired outputs from language models.
• Knowledge of finetuning techniques for language models, including methods to adapt and customize pretrained models for specific generative tasks, such as text generation, summarization, or dialogue systems.
• Public AI-related projects you have developed available on GitHub