Data Scientist

Roles & Responsibilities:

Develop and Implement Cutting-Edge Generative AI Models:

Spearhead the design and implementation of state-of-the-art generative AI models and algorithms using cutting-edge technologies such as PyTorch, Hugging Face, Spark, and LangChain.

End-to-End Machine Learning Model Development:

Lead the development lifecycle of machine learning models, ensuring a comprehensive approach from initial design through training, evaluation, validation, to seamless implementation.

Application Development with Advanced Models:

Design and develop applications that harness the power of Large Language Models (LLMs) and Feature Models (FMs), contributing to the creation of innovative and impactful solutions.

Develop strategic predictive models and algorithms to provide robust support for crucial business decision-making processes.

Collaborate closely with stakeholders to understand business requirements and translate them into effective and impactful machine learning solutions.

Engage effectively with stakeholders, ensuring alignment between technical developments and business goals.

Expertise in Model Optimization and Fine-Tuning:

Bring hands-on experience in optimizing and fine-tuning large language models, focusing on enhancing performance metrics such as speed, latency, memory utilization, and throughput.

Stay at the forefront of optimization techniques and implement them judiciously to ensure optimal model efficiency.

Required Qualifications of the Data Scientist:

Experience:

• Possess a minimum of 3 years of hands-on experience in the development of Machine Learning and Deep Learning algorithms.
• Demonstrate a proficiency of at least 1 year working with technologies including Large Language Models (LLMs), Generative AI (Gen AI), Langchain, EmbedChain, and Transformers.
• Showcase expertise in developing neural networks, with a strong command of either TensorFlow or PyTorch frameworks.
• Exhibit a robust knowledge base in Natural Language Processing (NLP), encompassing tools such as NLTK, Spacy, and expertise in models like BERT and SBERT.
• Proficient in forecasting technologies, showcasing expertise in Bayesian and Time Series algorithms.

Education:

Must be B. Tech and MCA with specialization of AI/ML or Computer Science, good in Statistics, Data Science, Mathematics