Vice President, AI / Machine Learning Data Engineering

BNY Mellon•New York, NY

1d•$69,000 - $200,000•Onsite

About The Position

We’re seeking a future team member for the role of Vice President, AI / Machine Learning Engineer to join our AI Hub team. This role is located in New York, NY. This role is located in our AI Hub and is focused on building AI-powered tools and platforms that improve the way engineers design, build, test, and operate software. This is a strong opportunity for a hands-on technical leader who can apply deep AI and software engineering expertise to deliver practical solutions, guide technical direction, and help scale high-value capabilities in an enterprise environment.

Requirements

Bachelor's degree in Computer Science, Data Engineering, or a related field or the equivalent combination of education and experience required.
5-9 years of experience in software development required; experience in the securities or financial services industry is a plus.
Advanced experience, preferably 8+ years, in applied AI/ML, model development, and software engineering, including experience building and deploying production solutions.
Ability to operate as a hands-on technical lead, collaborating with engineers and partners while helping drive design, implementation, and delivery decisions.
Strong understanding of enterprise software practices, MLOps / LLMOps, evaluation approaches, and how to create secure, scalable, and sustainable AI solutions.
Ability to communicate technical ideas effectively and work across a range of audiences, including engineers, product partners, and business stakeholders.

Responsibilities

Lead the design and development of applied AI solutions, providing hands-on technical leadership for machine learning and artificial intelligence products.
Bring strong knowledge of Applied AI, LLMs, fine tuning, model evaluation, and approaches to building fit-for-purpose models, copilots, and agents for engineering use cases.
Conduct technical research, prototyping, and experimentation to evaluate model and tooling approaches, and translate findings into actionable recommendations and implementation plans.
Partner with engineering and business stakeholders to understand priorities, workflows, and opportunities, and help define success measures that demonstrate developer and business impact.
Bring expertise in applying AI to improve the software development lifecycle and support builders, designers, and developers with secure, scalable, and production-ready capabilities.
Contribute to the achievement of Application Development objectives by mentoring engineers, promoting strong engineering practices, and supporting high-quality delivery across architecture, reliability, and responsible AI adoption.