Senior Staff Software Engineer

The ML Platform team is on a mission to build the core infrastructure that powers Affirm's intelligence.  Affirm uses machine learning to assess and approve each BNPL transaction. Affirm’s ML models answer questions like: is the applicant willing and able to repay this loan? 

The role of the ML Platform team is to build the compute platform for training and serving all of Affirm's ML models and features. Online, we operate a feature store and model server that enable real-time feature computation and model scoring. Offline, we manage an environment for running large scale model training and data analysis.

What You'll Do

• You will set the multi-year, multi-team technical strategy for ML Platform and deliver it through direct implementation or broad technical leadership
• You will partner with technical leaders across the company to create joint roadmaps that will achieve business impacting goals through the advancement of machine learning
• You will act as a force-multiplier for your teams through your definition and advocacy of technical solutions and operational processes
• You have an ownership mindset,  and you will proactively champion investments in availability so that every project in your area achieves its availability targets
• You will foster a culture of quality and ownership on your team by setting system design standards for your team, and advocating for them beyond your team through your writing and tech talks
• You will help develop talent on your team by providing feedback and guidance, and leading by example

What We Look For

• 10+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin.
• Strong experience leading multiple engineering teams to deliver high quality software
• Track record of successfully leading engineering teams at both rapidly scaling startups and complex larger technology companies.
• Expertise in synthesizing complex technical requirements, designs, trade-offs, and capabilities into clear decisions to influence ML & engineering direction
• Extensive experience developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes.
• Experience building and operating online, real-time ML infrastructure including a model server and a feature store
• Experience developing an offline environment for large scale data analysis and model training using technologies including Spark, Kubeflow, Ray, and Airflow
• Experience delivering major features and system components
• You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work.
• Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers.
• You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
• This position requires either equivalent practical experience or a Bachelor’s degree in a related field.

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000
USA base pay range (all other U.S. states) per year: $232,000 - $282,000


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