In this role as a Senior Gen AI Data Scientist in the Transformation team, you will collaborate with data scientists and stakeholders to understand business requirements and translate them into machine learning and generative AI solutions.

Responsibilities may include the following and other duties may be assigned:
Design, develop, and implement machine learning models and algorithms to solve complex business problems.
Use software design principles to develop production ready code.
Collect, preprocess, and analyze large datasets to train and evaluate machine learning models.
Optimize and fine-tune machine learning models for performance and accuracy.
Deploy machine learning models into production environments and monitor their performance.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Stay up to date with the latest advancements in machine learning and apply them to improve existing models and algorithms.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
Document and communicate machine learning solutions, methodologies, and results to technical and non-technical stakeholders.
Mentor and provide guidance to junior Gen AI Data Scientists.

Required Knowledge and Experience:
Strong understanding of ML algorithms and techniques: supervised, unsupervised learning, deep learning. Deep knowledge in NLP, Computer Vision, and GenAI, including architectures like Transformers, BERT, GPT.
7+ years of industry experience in writing production level, scalable code (e.g. in Python)
7+ years of industry experience with popular ML frameworks such as PyTorch, Scikit-learn, NLTK, Hugging Face Transformers, and others (e.g. Langchain, Lang Graph).
5+ years of industry experience with distributed computing frameworks such as PySpark.
5+ years of experience with full-stack web development (using either Python backend + React frontend or AI builders like replit.com, lovable.dev, builder.io).
5+ years of experience in building and scaling Generative AI applications, vector DB, Agentic and RAG applications.
Experience in deploying, monitoring, finetuning, evaluating LLM/VLM models and building AI agents.
5+ years of industry experience with major cloud computing services like AWS or Azure or GCP.
Bachelors or Masters degree in a quantitative field: Computer Science, Engineering, Statistics, Mathematics, or related field.

Preferred Qualifications:

Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
Proficient in containerization services.
Proficient in Bedrock or Databricks ML to deploy the models.
Experience with orchestration tools and CICD framework.
Experience in deploying and scaling open source LLM Models