Posted:12 hours ago|
Platform:
On-site
Full Time
Key Responsibilities-
• Build Gen AI-enabled solutions using online and offline LLMs, SLMs and TLMs tailored to
domain-specific problems.
• Deploy agentic AI workflows and use cases using frameworks like LangGraph, Crew AI etc.
• Apply NLP, predictive modelling and optimization techniques to develop scalable machine
learning solutions.
• Integrate enterprise knowledge bases using Vector Databases and Retrieval Augmented
Generation (RAG).
• Apply advanced analytics to address complex challenges in Healthcare, BFSI and
Manufacturing domains.
• Deliver embedded analytics within business systems to drive real-time operational insights.
Required Skills & Experience
• 3–5 years of experience in applied Data Science or AI roles.
• Experience working in any one of the following domains: BFSI, Healthcare/Health Sciences,
Manufacturing or Utilities.
• Proficiency in Python, with hands-on experience in libraries such as scikit-learn, TensorFlow
• Practical experience with Gen AI (LLMs, RAG, vector databases), NLP and building scalable
ML solutions.
• Experience with time series forecasting, A/B testing, Bayesian methods and hypothesis
testing.
• Strong skills in working with structured and unstructured data, including advanced feature
engineering.
• Familiarity with analytics maturity models and the development of Analytics Centre of
Excellence (CoE’s).
• Exposure to cloud-based ML platforms like Azure ML, AWS SageMaker or Google Vertex AI.
• Data visualization using Matplotlib, Seaborn, Plotly; experience with Power BI is a plus.
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