You Lead the Way. We’ve Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers’ digital lives.  Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems.  Amex offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source.  And because we understand the importance of keeping your skill fresh and relevant, we give you dedicated time to invest in your professional development.  Find your place in technology on #TeamAmex.  

Let’s share success.

Global Infrastructure Product Services aims to establish and reinforce a culture of effective metrics, data-driven business processes, architecture simplification, and cost transparency. 

As the Data Science team in Global Infrastructure Product Services embarks on building and deploying machine learning(ML) models, we are looking for a senior machine learning engineer (MLE) to build /utilize robust date andMLOps pipelines to deploy and monitor models in prouction.

A successful MLE knows that delivering on that promise takes foresight, planning and agility.  We are seeking MLEs who are not only technically adept, but also understand the importance of harnessing the power of MLOps to streamline financial operations, enhance decision-making and improve business outcomes. 

This team is focused on developing and maintaining dynamic technology infrastructure cost allocation and projection models. The financial forecasting models will help ensure that our technology spending is transparent, efficient, and properly aligned with our strategic objectives. The role requires a blend of technical prowess in data engineering, data science, MLOps, and an understanding of enterprise infrastructure components & their economics.

Let’s build on what you know.

If you are a pioneer in developing robust  data pipelines and deploying machine learning models in production that drive and monitor infrastructure cost and consumption analysis, you'll find a fit within our Data Science team in Global Infrastructure Product Services. To succeed in this newly forming team, you'll need to be comfortable navigating ambiguity to stand up solutions 0à1 while discovering and leveraging enterprise platforms and best practices.

Here’s just some of what you’ll do:

Create robust data pipelines that feed machine learning models in production and retraining. Design and deploy scalable solutions in AI and Machine Learning for financial forecasting and optimizing infrastructure resource utilization & lifecycle tracking to help further mature our FinOps and AIOps framework Ensure best practices are aligned with Enterprise Architecture and ML COEs. Deploy AI and Gen AI solutions to drive automation and optimization of Enterprise Infrastructure Assets and workflows. Work closely with stakeholders across Technology, Finance and business unit portfolio leaders to define data and analytics requirements and incorporate cost drivers, allocation methods, and infrastructure nuances Develop SQL queries, scripts and routines to automate data processing and enhance the model’s accuracy and efficiency Drive high-level and detailed technical design conversations and reviews Be responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, code reviews and CI/CD tool integration Lead training sessions and create comprehensive documentation to empower end users to leverage the cost model effectively Generate insightful data visualization and reports to aid in decision-making Function as an active member of an agile team Provide technical mentorship to team members at junior levels

Are you up for the challenge?  Here’s what you should have:

Demonstrated experience in MLOps on Vertex AI and Azure machine learning including but not limited to automated data and machine learning pipelines that allow model retraining and continuous monitoring Hands-on expertise with distributed (multi-tiered) systems and automated testing – unit and performance testing Proficiency with Git, CI/CD tools, Containers (Docker) and orchestration (Airflow, Astronomer, Kubernetes) Strong proficiency in Python language, machine learning libraries and SQL Demonstrated experience in building and deploying a diverse set of ML models (GLM, GBM, Neural Networks) and NLP solutions at scale Experience in deploying out-of-the box LLMs and Generative AI solutions, and some familiarity with LLMOps Experience in data visualization and observability with a focus on real time serving and monitoring of time series data with alerts Thorough understanding of enterprise infrastructure technologies (Compute, Storage, Network, Mainframe) to inform model development Experience in knowledge graphs is a plus Strong project management skills and effective stakeholder management skills coupled with a continuous improvement mindset Excellent presentation and communication skills, capable of explaining complex technical choices in simple terms to a diverse audience Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related STEM discipline is a plus Experience in Financial Services industry is preferred

 

Salary Range: $110,000.00 to $190,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

Competitive base salaries  Bonus incentives  6% Company Match on retirement savings plan  Free financial coaching and financial well-being support  Comprehensive medical, dental, vision, life insurance, and disability benefits  Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need  20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy  Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)  Free and confidential counseling support through our Healthy Minds program  Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

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Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.