Senior Machine Learning Platform Engineer, ML Foundations

Company Description

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

Job Description

About machine learning

ML is essential to Block's daily operations and long term success. Its usage has grown dramatically over the past few years and is only accelerating. As more teams integrate ML capabilities, so has the need to avoid duplication by providing shared capabilities.

About the team

Machine Learning Foundations (MLF) builds scalable, composable components for ML use cases. We work closely with platform and product teams across the company to amplify their growth by solving complex problems that impact multiple business groups. Block's ML community is too large and moves too quickly for MLF to stay ahead of such a diverse set of needs, so we target a narrower set of use cases that will have an outsized impact on our internal customers.

About the role

We are looking for an experienced engineer to join MLF. While your initial focus will be building self-service tooling for the model lifecycle, particularly model deployments, serving, and monitoring, you will also have opportunities to work across the entire machine learning lifecycle. As a platform engineer, you will work closely with our internal customers to understand their needs and translate those into sustainable software solutions.

We are looking for someone who has experience primarily as a machine learning engineer or modeler, as well as a software engineer, as we operate at the intersection of those two roles. Candidates must demonstrate professional experience with the end-to-end ML lifecycle, and we prefer candidates who also have experience building platforms. Beyond that:

You will

• Design and build tools and systems that make data scientists happier and more productive
• Work closely with data science and engineering teams across Block, particularly Cash and Square, to understand their needs and solve their problems
• Lead architectural and design discussions to ensure our platform is modular, scalable, fault tolerant, and sustainably built
• Mentor your teammates and assist engineers on other teams who integrate with our platform
• Leverage your machine learning knowledge by providing insightful feedback
• Participate in an oncall rotation; maintain exceptional reliability standards while ensuring the team's oncall rotation is sustainable

Qualifications

You have

• 8+ years of combined experience in software engineering and machine learning engineering
• 5+ years of experience with the ML lifecycle, such as feature engineering, model training, etc.
• Strong technical judgment and meaningful experience handling complex technical concepts
• Experience with large-scale distributed systems built around ML
• A track record of healthy collaboration with product managers, engineers, and other stakeholders
• Preferred: experience building machine learning platforms or infrastructure

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $198,000 - USD $297,000
Zone B: USD $188,100 - USD $282,100
Zone C: USD $178,200 - USD $267,400
Zone D: USD $168,300 - USD $252,500

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Full-time employee benefits include the following:

• Healthcare coverage (Medical, Vision and Dental insurance)
• Health Savings Account and Flexible Spending Account
• Retirement Plans including company match 
• Employee Stock Purchase Program
• Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance 
• Paid parental and caregi