A Great Place To Work: LLM's Data Scientist - Factspan Analytics

Position: LLM's ( Gemini, GPT, PaLM, or similar frameworks) Data Scientist - Factspan Analytics : A Great Place To Work

Qualifications:

• Bachelors degree (Engineering - Must) in a related field or equivalent experience
• Minimum of 6 years of related AI/ML work experience

This is a full-time, permanent role.

For inquiries, contact sathishkumar.arumugam@factspan.com

Responsibilities

We are seeking a highly skilled and motivated Principal / Senior Principal Analyst to join our team. The ideal candidate will possess a strong technical background with expertise in various programming languages and data technologies, Data Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a Analyst (Technical) , you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Preferred candidate profile

• Develop and fine-tune applications using Gemini LLM and other state-of-the-art NLP models.
• Integrate Gemini LLM capabilities into existing platforms and create new, AI-driven solutions.
• Design and implement efficient pipelines for training, evaluating, and deploying LLM-based applications.
• Work with cross-functional teams to identify business use cases and translate them into technical solutions powered by LLMs.
• Optimize model performance, latency, and scalability for production-grade deployments.
• Conduct research on emerging trends in NLP and LLM technologies to drive innovation within the team.
• Develop APIs and services to expose LLM capabilities to internal and external users.
• Monitor deployed models, analyze their performance, and iteratively improve them based on user feedback and operational data.
• Ensure adherence to ethical AI guidelines and implement robust measures for model explainability, fairness, and security.
• Proven experience with LLMs such as Gemini, GPT, PaLM, or similar frameworks.
• Hands-on experience in NLP and machine learning, including language model training, fine-tuning, and deployment.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and LangChain.
• Experience with cloud platforms like Google Cloud (Vertex AI), AWS, or Azure for deploying AI solutions.
• Familiarity with MLOps tools for managing models in production environments.
• Understanding of prompt engineering, embedding generation, and model evaluation metrics for LLMs.