Your Role and Responsibilities

Machine Learning Model Development: Design, develop, and implement machine learning models using Python libraries such as TensorFlow, PyTorch, or scikit-learn.

Large Language Model Integration: Collaborate with architects to leverage Large Language Models (LLMs) like Watsonx AI, GPT-4, or Bedrock (if applicable) for project success.

GenAI Project Experience: Bring at least 2 years of experience in GenAI projects, either for clients or IBM assets/products.

GenAI Task Expertise: Demonstrate expertise in at least one GenAI task, such as:

RAG content generation

Code generation

Code conversion

AI Agent development

Data mapping

Graph RAG

Solution Design and Requirements: Work closely with business SMEs to define project requirements, select appropriate AI/ML/GenAI models with architects, and set realistic model benchmarks to meet business needs.

AI Solution Design with Ethics: Collaborate with architects to design AI solutions that incorporate knowledge of AI ethics.

Required Technical and Professional Expertise

Machine Learning and GenAI: Strong understanding of machine learning and GenAI concepts. Awareness of ethical implications in GenAI, including bias, fairness, and privacy.

Python and Data Science Libraries: Proficiency in Python and relevant data science libraries (e.g., NumPy, Pandas, scikit-learn). Practice on Graph database and Vector DB.

Large Language Models: Familiarity with LLMs, including their architectures, capabilities, and limitations. Skill in crafting effective prompts to guide LLMs and obtain desired outputs. Ability to handle and prepare data for analysis, including data cleaning, normalization, and feature engineering

GenAI Frameworks: Deep understanding of GenAI frameworks like TensorFlow, PyTorch, Hugging Face Transformers, Langchain, and Llama index.

Latest GenAI Practices: Knowledge of the latest GenAI practices on at least two prominent LLMs (e.g., GPT-4, Llama3).

Preferred Technical and Professional Expertise

Knowledge of Model Ops practices on cloud and containerization

Familiarity with design lead development methodologies in complex data platforms and analytics

Ability to work with data from the data platform and communicate insights effectively.