Data Scientist

Asset Engineering is looking for a motivated and seasoned Data Scientist and Machine Learning Engineer to join our global team to deliver outstanding results for both internal/external clients. You will be working in one of our top 10 most prized assets called Modern Data Accelerators. This product provides the foundation of data and analytics to harness the power of our clients’ data within their enterprises.  MDA provides software tools for data, including curation, ingestion, operational controls, persist & publish, data product creation, governance, and data security. You will directly collaborate with the CTO of the asset and the technical team who architect, develop, enhance, and govern the asset.

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.