Senior Machine Learning Engineer - Infra/Ops - Fraud

United States Digital Space LLC; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity

Commission

Benefits: medical, dental, vision, 401

Job summary

United States Digital Space LLC is pursuing a Senior Machine Learning Engineer to own high-performance feature computation and online inference pipelines for production ML systems at scale.

You will build observability and automated debugging, partner with ML Infrastructure and Data Science teams, and deliver scalable ML solutions across the fraud domain.

Qualifications

• Experience building, deploying and scaling production ML systems.
• Proficiency in Python and ML/data technologies (PyTorch, Spark, SageMaker, Airflow).
• Ability to own end-to-end ML projects independently.

Responsibilities

• Build and scale ML systems powering fraud-detection products.
• Solve complex ML infra challenges in data-intensive environment.
• Develop foundational ML capabilities from financial network data to detect fraud.
• Collaborate with engineers, data scientists, and product teams to deliver high-impact solutions.

Skills

Python

PyTorch

Spark

SageMaker

Airflow

Tools

Kubernetes

Docker

Job description

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. the company powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. the company's network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.

The Data team within the company's Fraud organization builds the machine learning systems that power the company's fraud detection products, leveraging the company's unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers.

As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You'll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You'll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions.

Responsibilities:

• Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment.

• Solve complex technical challenges at the intersection of machine learning, data infrastructure, and production reliability.

• Develop foundational ML capabilities that leverage the company's extensive financial network data to detect and prevent fraud.

• Collaborate closely with engineers, data scientists, and cross-functional partners across the company to deliver high-impact solutions.

Qualifications:

• 6+ years of relevant experience, with a strong focus on building, deploying, and scaling production machine learning systems.

• Strong experience with ML infrastructure and operations, including production deployment, monitoring, and reliability.

• Proven ability to independently own and deliver complex, end-to-end machine learning engineering projects.

• Proficiency with Python and experience with ML and data technologies such as PyTorch, Spark, SageMaker, and Airflow.

Nice-to-Have:

• Experience in fraud or risk domains.

• Experience in Graph machine learning.

Our mission at the company is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to the company!

the company is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. the company is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at [e-mail].

Please review our Candidate Privacy Notice here.

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. the company provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.