Senior AI Solutions Engineer VP - P4

Morgan Stanley • New York, NY

8h

About The Position

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. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser. Expected base pay rates for the role will be between $150,00 and $210,000 per year at the commencement of employment. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees. It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

Requirements

• Master's or PhD in Computer Science, Mathematics, Engineering, Statistics or a related field
• Proven experience building and deploying to production GenAI models with demonstrable business value realization
• 5+ years' 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 etc.)
• 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

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees