Lead LLM Data Scientist
2 weeks ago
Founded in the year 2017, CoffeeBeans specializes in offering high end consulting services in technology, product, and processes. We help our clients attain significant improvement in quality of delivery through impactful product launches, process simplification, and help build competencies that drive business outcomes across industries. The company uses new-age technologies to help its clients build superior products and realize better customer value.
We also offer data-driven solutions and AI-based products for businesses operating in a wide range of product categories and service domains. We are seeking a highly skilled Data Scientist with a strong background in building AI-powered products using Large Language Models (LLMs) such as OpenAI's GPT models, Llama, etc.
In this role, you will leverage your expertise in deep learning, machine learning, and natural language processing (NLP) to develop and optimize scalable, innovative solutions for complex problems. Key Responsibilities:Analyze and interpret complex data sets using Python and SQL, providing insights that influence business decisions. Design, implement, and maintain deep learning pipelines to build and optimize AI-powered products.
Collaborate with cross-functional teams to define data science needs, establish strategies, and develop scalable solutions using state-of-the-art LLMs. Fine-tune and adapt LLMs to solve domain-specific problems, continually improving model performance and accuracy. Conduct advanced research, experimentation, and iteration on LLM architectures, performance metrics, and deployment strategies.
Stay abreast of the latest developments in AI, machine learning, NLP, and LLM research, applying cutting-edge techniques to business challenges. Required Qualifications:Education: Bachelor's degree in Computer Science, Data Science, or a related field from a top-tier institution (e.g., IIT). Skills & Tools:Strong proficiency in Python and SQL for data analysis, model development, and automation.
Hands-on experience working with open source LLMs. Deep understanding of machine learning principles, natural language processing (NLP), and AI technologies. Proven ability to develop, fine-tune, and deploy AI-powered products using LLMs.
Experience:8-10 years of experience in data science roles, with a focus on AI, machine learning, and large language models. Demonstrated track record of developing and deploying products powered by machine learning and AI.Preferred Skills:Familiarity with cloud-based AI services like AWS SageMaker, Google AI Platform, or Azure Machine Learning. Experience with MLOps tools such as MLflow, Kubeflow, or Airflow to streamline and scale machine learning workflows.
Knowledge of deep learning frameworks like TensorFlow or PyTorch. Familiarity with model evaluation metrics and techniques to ensure continuous improvement and performance optimization.
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