Senior Specialist, AI / Machine Learning Data Engineer

BNY Mellon•New York, NY

1d•$59,000 - $113,000•Onsite

About The Position

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 an exciting opportunity for a strong individual contributor who can apply AI and software engineering skills to develop practical solutions, contribute to technical innovation, and help deliver scalable capabilities in support of engineering teams.

Requirements

Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required.
2-6 years of experience in software development required; experience in the securities or financial services industry is a plus;
Advanced experience, preferably 5+ years, in applied AI/ML, software engineering, or model development, including experience building and testing production-oriented solutions.
Ability to work independently as a strong technical contributor while collaborating closely with peers and senior engineers on solution design and delivery.
Strong understanding of software engineering fundamentals, enterprise development practices, and modern AI/ML tooling, with an interest in scalable and sustainable architectures.
Ability to communicate technical concepts clearly, learn quickly, and work effectively with both technical and non-technical stakeholders.

Nice To Haves

experience in the securities or financial services industry is a plus

Responsibilities

Design, develop, and support applied AI solutions, contributing hands-on to machine learning and artificial intelligence products and features.
Bring solid knowledge of Applied AI, LLMs, prompt engineering, fine tuning, model evaluation, and approaches to building fit-for-purpose models and copilots for engineering use cases.
Perform technical research, experimentation, and prototyping to evaluate tools, frameworks, and model approaches, and help translate results into implementation recommendations.
Partner with engineers and stakeholders to understand requirements, workflows, and user needs, and contribute to success measures that demonstrate solution value and adoption.
Apply AI to improve the software development lifecycle and support builders, designers, and developers through reliable, secure, and effective tools and capabilities.
Contribute to the achievement of Application Development objectives by delivering high-quality engineering work, supporting team standards, and continuously building technical depth across AI and software engineering practices.