Back
Tier-1 brand, mid-level ML role, metro location, and popular data science title increase applicant competition.
ML/NLP skills transferable across industries, with moderate sensitivity to finance domain knowledge.
Specific ML/LLM skills and a preferred 5+ years make screening moderately strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Assist in development, fine-tuning, and deployment of generative AI and large language models.
Prepare and preprocess large datasets; customize and fine-tune Retrieval-Augmented Generation (RAG) frameworks.
Conduct research experiments to test model performance and collaborate with cross-functional teams to integrate AI models into applications.
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 including linear algebra, calculus, and probability.
Work Experience Required: 5+ years in data science, machine learning, or related field (preferred).
Experience with AI/ML projects including deployment of machine learning models in production environments.
Familiarity with cloud platforms such as AWS, Google Cloud, or Azure, and version control systems like Git.
Ability to analyze complex problems and communicate technical concepts effectively to both technical and non-technical stakeholders.