Morgan Stanley is looking to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm’s Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.
Requirements
- Strong hands-on proficiency in Python and machine learning specific libraries like numpy, opencv, scikit-learn, pandas, matplotlib, seaborn, etc.
- Understanding of AI/ML Lifecycle and basic understanding of systems like mlflow, Dataiku, databricks.
- Broad understanding of data engineering (SQL, NoSQL, Big Data), data governance, data privacy and security
- Demonstrated experience in DevOps, understanding of CI/ CD. Hands on experience with managing code in code repositories such as Bit Bucket and GitHub.
- Understanding of how deep learning works, understanding of Machine Learning frameworks such as TensorFlow or PyTorch
- Experience developing GenAI applications
- Experience working with cloud providers, preferably Azure, but also AWS, GCP
Responsibilities
- Build Proof of Concepts and example code through which developers can leverage GenAI models to solve common problems or patterns to enable GenAI adoption at scale
- Develop prototypes to demonstrate model capabilities, advanced usage patterns.
- Collaborate with AI engineers to prioritize capabilities for firmwide platform roadmap
- Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain, and Sematic Kernel.
- Troubleshoot customer adoption of genAI platform capabilities; update user documentation and provide feedback to platform engineering teams to improve future customer experience
- Have an application developer mindset and build common, reusable solutions to scale Generative AI use cases using pre-trained models as well as fine-tuned models.
- Develop patterns and best practices to enable GenAI application adoption at scale
Other
- Bachelor’s or Master’s degree in computer science or related field, or equivalent job experience
- 8 - 12 years of experience in software engineering, design, and development
- Excellent soft communications skills are mandatory
- Ability to articulate technical concepts effectively to diverse audiences.
- Strong desire and ability to influence development teams and help them adopt AI.
