Senior Data Scientist

In this specialised role, you will leverage your expertise in machine learning and statistics to derive valuable insights from data. Your role will include developing predictive models, interpreting data and working closely with our ML engineers to ensure the effective deployment and functioning of these models

Responsibilities:

Lead cross-functional teams in the design, development, and deployment of Generative AI solutions, with a strong focus on Large Language Models (LLMs).

Architect, train, and fine-tune state-of-the-art LLMs (e. g., GPT, BERT, T5) for various business applications, ensuring alignment with project goals.

Deploy and scale LLM-based solutions, integrating them seamlessly into production environments and optimising for performance and efficiency.

Develop and maintain machine learning workflows and pipelines for training, evaluating, and deploying Generative AI models, using Python or R, and leveraging libraries like Hugging Face Transformers, TensorFlow, and PyTorch.

Collaborate with product, data, and engineering teams to define and refine use cases for LLM applications such as conversational agents, content generation, and semantic search.

Design and implement fine-tuning strategies to adapt pre-trained models to domain-specific tasks, ensuring high relevance and accuracy.

Evaluate and optimise LLM performance, including handling challenges such as prompt engineering, inference time, and model bias.

Manage and process large, unstructured datasets using SQL and NoSQL databases, ensuring smooth integration with AI models.

Build and deploy AI-driven APIs and services, providing scalable access to LLM-based solutions.

Use data visualisation tools (e. g., Matplotlib, Seaborn, Tableau) to communicate AI model performance, insights, and results to non-technical stakeholders.

Secondary Responsibilities:

Contribute to data analysis projects, with a strong emphasis on text analytics, natural language understanding, and Generative AI applications.

Build, validate, and deploy predictive models specifically tailored to text data, including models for text generation, classification, and entity recognition.

Handle large, unstructured text datasets, performing essential preprocessing and data cleaning steps, such as tokenisation, lemmatisation, and noise removal, for machine learning and NLP tasks.

Work with cutting-edge text data processing techniques, ensuring high-quality input for training and fine-tuning Large Language Models (LLMs).

Collaborate with cross-functional teams to develop and deploy scalable AI-powered solutions that process and analyse textual data at scale.

Key Success Metrics:

Ensure timely deliverables.

Spot Training Infrastructure fixes.

Lead technical aspects of the projects.

Error-free deliverables.

Requirements:

B. E/B. Tech University (Premier/ Tier1 II, III, Others).

Post Graduate Degree: M. Tech, Tier1

Professional Degree: Any B. E/B. Tech University (Premier/Tier 1 II, III, Others).

Technical Skills:

Data Processing: Apache Spark, Apache Hive, etc.

Data Modelling: Tensorflow, Pytorch, HuggingFace.

Training Infrastructure: GPU Training/AWS Sagemaker/Azure.

Databases: Apache Airflow, Control-M, etc.

Programming/ Scripting Language: Python, PySpark, Unix.

Functional Skills:

Textual Model Architecture: Transformers, BERT, RNN, LSTMS, Embeddings.

Neural Networks: (Proficiency Level -High).