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Tier-1 brand, mid-level ML title, metro location, and broad AI skill requirements increase competition.
Medium because ML/LLM skills transfer across industries but banking production and domain familiarity increase bias.
High due to explicit 5+ years preference and mandatory ML/LLM production, cloud, and framework experience.
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Develop, fine-tune, and deploy generative AI and large language models, ensuring data preparation and customization of RAG frameworks to meet project needs.
Conduct research, experiments, and performance optimization to improve model accuracy, efficiency, and scalability.
Collaborate with cross-functional teams to integrate AI models into applications, while maintaining clear documentation of architectures and processes.
Bachelor’s degree in Computer Science, Data Science, Electrical Engineering, or related field; Master’s degree is a plus.
Proficiency in Python and familiarity with machine learning libraries/frameworks like TensorFlow, PyTorch, Hugging Face Transformers.
Strong understanding of mathematics and statistics fundamentals (linear algebra, calculus, probability).
Work Experience Required: 5+ years in data science, machine learning, or related field; experience with AI/ML projects or internships.
Experienced in deploying machine learning models in production and working with cloud platforms (AWS, Google Cloud, Azure).
Skilled in customizing and fine-tuning RAG frameworks and generative AI/LLM technologies with a research-oriented approach.
Capable of communicating technical concepts effectively to non-technical stakeholders, supporting cross-team collaboration and documentation.