MResult - Lead Data Scientist - NLP/Deep Learning/Machine Learning (7-15 yrs)

Requirements and skills :

- Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field.

- Minimum of 3-5 years of experience in NLP-oriented data engineering or data science roles with a significant emphasis on working with ML, DL, and LLM/Generative AI models.

- Must have strong experience in NLP/NLG/NLU applications using popular machine learning algorithms such as Logistic Regression, Clustering, Boosting, Bagging models, and LLMs, etc.

- Must have proven experience in understanding and building Gen AI, LLM models. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM

model development, fine-tuning, prompt engineering, and ensuring the solution meets all technical and business requirements.

- Proficiency in Python programming and familiarity with libraries and frameworks such as Pandas, Scikit learn, PyTorch, TensorFlow, BERT, GPT (or similar models), and Langchain.

- Demonstrated ability to engage with client stakeholders at multiple levels and provide consultative solutions across different domains.

- Excellent analytical and problem-solving skills, capable of working independently and collaboratively in a team-oriented environment.

Responsibilities :

- Participate as part of a project team and collaborate with cross-functional teams to design, code, test, and implement programs.

- Play a central role in all stages of the AI-based product development life cycle.

- Train, validate, and test the appropriate machine learning models in an AWS environment.

- Solve complex NLP problems using advanced machine learning algorithms, NLP, and statistics: Classification, clustering, decision trees, ensemble modelling, neural networks, etc.

- Design and develop custom ML, Gen AI, NLP, LLM models; Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development,

fine-tuning, prompt engineering, and ensure the solution meets all technical and business requirements.

- Work closely with other members of the data science, MLOps, and technology teams in the design, development, and implementation of the ML model solutions.

- Work as part of an agile team to identify and deliver solutions to prioritized requirements.

- Keep up to date with the latest industry trends and technologies.