Project/ Task

Design, develop, and optimize LLMs for various NLP applications

Create and refine conversation prompts to improve AI system interactions

Collaborate with cross-functional teams to integrate LLMs and prompts into AI applications.

Conduct research to enhance model performance and user experience

Analyze data to identify patterns and trends in user interactions and model performance

Stay up-to-date with the latest advancements in deep learning, NLP, and LLMs

Mentor junior engineers and provide technical guidance

Participate in code reviews and provide constructive feedback to team members

Document processes, research findings, and model development.

Stay abreast of industry trends and advancements in AI/ML technology.

Support the team in identifying opportunities for leveraging client data to drive business solutions.

Qualification

Bachelor's degree in computer science, engineering, or a related field

years of experience in deep learning and NLP, with a focus on LLMs

Proficiency in programming languages such as Python, Java, or C

Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras

Strong understanding of NLP libraries and tools such as NLTK, spaCy, or Hugging Face

Demonstrated experience in prompt engineering and optimizing LLMs

Strong analytical and problem-solving skills

Excellent communication and interpersonal skills

Ability to work independently and as part of a team

Experience with cloud platforms such as AWS or Azure is a plus

Technology

Data Bricks, Domino Data, Palantir AWS, Azure, Google Cloud Platform, Data Modeling, Data Architecture, ML/AI/ LLM, dbt, Snowflake

Skill Set Experience with cloud services (AWS, Google Cloud Platform, or Azure) is a plus.

Knowledge of SQL and experience working with databases.

Exposure to big data technologies (e.g., Hadoop, Spark).

A passion for AI/ML and staying updated with the latest developments in the field.

Preferred Qualifications:

Master's degree or PhD in computer science, engineering, or a related field

Experience with large language models (LLMs) like GPT, BERT, etc.

Knowledge of linguistics or cognitive science

Publications or contributions to the field of deep learning, NLP, or LLMs