Requirements
- 3+ years of experience in Data Science and Artificial Intelligence.
- Knowledge and experience in Generative AI (GenAI) including Agentic AI.
- Proficiency in Python programming language and frameworks like TensorFlow, PyTorch, Pandas or Scikit-Learn.
- Knowledge of at least one framework like LangChain, LangGraph, AutoGen, Semantic Kernel or other.
- Strong understanding of Natural Language Processes (NLP) techniques such as tokenization, string comparison and embeddings.
- Experience with cloud platforms such as Azure, AWS or GCP.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Nice to Have
- Hands-on experience with tools such as Docker, Kubernetes, and Git or Azure DevOps to build and manage AI pipelines including MLOps practices, covering CI/CD, and monitoring of AI.
- Know trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
- Implement monitoring and logging tools to ensure AI model performance and reliability.
- Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
- Demonstrate excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
Benefits
- Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
- Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
- Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
- Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.
Work Arrangement
Hybrid
