Morgan Stanley is hiring a Vice President – Senior AI Solutions Engineer. In this role, you will design, architect, and optimize data-intensive systems with a focus on Generative AI, LLMs, traditional AI, and NLP. You will work on projects leveraging large volumes of structured and unstructured data, integrating Knowledge Graphs and Multiagent systems to deliver business value.
What You'll Do
- Design and develop state-of-the-art GenAI and general AI solutions as well as multiagent systems to solve complex business problems.
- Integrate knowledge graph, LLMs and multiagent systems.
- Leverage NLP techniques to enhance applications in language understanding, generation, and other data-driven tasks.
- Lead the design and architecture of scalable, efficient, and high-performance data systems that support processing of massive datasets of structured and unstructured data.
- Use machine learning frameworks and tools to train, fine-tune, and optimise models. Implement the best practices for model evaluation, validation, and scalability.
- Stay up to date with the latest trends in AI, NLP, LLMs and big data technologies. Contribute to the development and implementation of new techniques that improve performance and innovation.
- Collaborate with cross-functional teams, including engineers, product owners, and other stakeholders to deploy AI models into production systems and deliver value to the business.
- Leverage a strong problem-solving mindset to identify issues, propose solutions, and conduct research to enhance the efficiency of AI and machine learning algorithms.
- Communicate complex model results and actionable insights to stakeholders though compelling visualizations and narratives.
What We're Looking For
- B.E or Master’s or PhD in Computer Science, Mathematics, Engineering, Statistics or a related field.
- 12+ years of total working experience.
- At least 8 years of relevant experience.
- Proven experience building and deploying to production GenAI models with demonstrable business value realization.
- 8+ years of experience in traditional AI methodologies including deep learning, supervised and unsupervised learning, and various NLP techniques (e.g., tokenization, named entity recognition, text classification, sentiment analysis).
- Strong proficiency in Python with deep experience using frameworks like Pandas, PySpark, TensorFlow, XGBoost.
- Demonstrated experience dealing with big-data technologies and the ability to process, clean and analyse large-scale datasets.
- Experience designing and architecting high-performance, data-intensive systems that are scalable and reliable.
- Strong communication skills to present technical concepts and results to both technical and non-technical stakeholders. Ability to work in a team-oriented and collaborative environment.
- Experience with Prompt Engineering, Retrieval Augmented Generation (RAG), Vector Databases.
- Strong understanding of multiagent architectures and experience with frameworks for agent development.
- Knowledge of Semantic Knowledge Graphs and their integration into AI/ML workflows.
Technical Stack
- Python, Pandas, PySpark, TensorFlow, XGBoost
- Generative AI, Large Language Models (LLMs)
- Natural Language Processing (NLP)
- Knowledge Graphs, Multiagent systems, Vector Databases
Team & Environment
This role is part of the Firmwide Data Office, Data COE team distributed globally between New York, London, Budapest, India, and Shanghai. We foster a culture of experimentation and constantly strive for improvement and learning. Our environment is collaborative, trusting, and thought-provoking, encouraging diversity of thought and creative solutions.
Work Mode
This position is local-country in India.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.
