AI ML Engineering Lead - Vice President - AI for Payments
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 1mo ago
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Job Location
Jersey City, NJ, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Join a team applying modern artificial intelligence and machine learning to high-impact, high-scale payments workflows. You will work with large datasets and complex operational processes to deliver measurable outcomes, building production-grade solutions spanning natural language processing, document understanding, and LLM-enabled applications. You will collaborate closely with business and technology partners to take ideas from concept to deployment, while also raising engineering standards and mentoring others. As a Vice President in the Wholesale Payments Operations team, you will build and deliver enterprise AI/ML solutions that improve operational efficiency and decisioning, partnering with senior stakeholders to frame problems, define success metrics, and plan roadmaps. You will design, implement, and deploy production services on Amazon Web Services (AWS) with strong engineering rigor, establishing model governance, monitoring, and responsible AI practices. The role focuses on building scalable AI/ML capabilities for operations use cases, including document processing and workflow automation, contributing to reusable platforms and patterns.
Responsibilities
- Partner with senior business stakeholders to frame problems, define success metrics, and align AI/ML roadmaps to priorities.
- Lead architecture, design, and end-to-end delivery of enterprise AI/ML solutions for Wholesale Payments Operations.
- Write clean, performant, production-quality code and set engineering standards across the team.
- Champion modern software development life cycle (SDLC), continuous integration and continuous delivery (CI/CD), and DevOps practices.
- Deploy and operate AI/ML services on AWS at scale.
- Apply advanced techniques including data/text mining, document analysis, classification, optical character recognition (OCR), natural language processing (NLP), and LLM workflows (including retrieval-augmented generation and fine-tuning).
- Design and implement scalable, secure data pipelines to support model training and inference.
- Define and enforce MLOps, model governance, monitoring, and responsible AI practices; represent the team in architecture and risk forums.
- Evaluate model performance in production, including drift management and reproducibility.
- Mentor engineers, conduct code and design reviews, and support recruiting and talent development.
Requirements
- Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 6 years of professional software engineering experience delivering production systems.
- 4 years of advanced Python development in production environments, including use of AI-assisted coding tools.
- 4 years of hands-on experience designing and deploying production machine learning systems on Amazon Web Services (AWS).
- Demonstrated experience delivering AI/ML solutions with measurable business outcomes at scale.
- Experience with object-oriented design, distributed systems, and performance engineering.
- Demonstrated experience building and deploying LLM-based applications, including retrieval-augmented generation and fine-tuning workflows.
- Hands-on experience in natural language processing (NLP), computer vision, optical character recognition (OCR), or document AI solutions in production.
- Experience implementing MLOps practices using tools such as MLflow, Kubeflow, Airflow, feature stores, or model registries.
- Demonstrated experience mentoring engineers and driving execution against multi-quarter roadmaps.
- Strong communication skills, including translating business needs into technical deliverables for senior stakeholders.