Staff Machine Learning Engineer, Modeling

Company Description

Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to take a payment and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, run a busy kitchen, book appointments, engage loyal buyers, and hire and pay staff. And across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow all in one place.

Today, we’re a partner to sellers of all sizes – large, enterprise-scale businesses with complex commerce operations, sellers just starting out, as well as merchants who began selling with Square and have grown larger over time. Whether it’s the food truck that’s establishing a brick & mortar restaurant, the former sole proprietor adding her first employees, or the entrepreneur expanding from one location to ten, as our sellers scale, so do our solutions. We all grow together.

Job Description

You will join a growing team of machine learning engineers in Square’s Automation organization which is a cross-functional team that accelerates Square sellers’ path to value realization by making technology investments that reduce friction and cost and increase personalization across customer interfaces.

Within the Seller Experience org, the ML team works closely with Data Science, Data Engineering, Business Intelligence, Product Management and Software Engineering teams to inject intelligence and efficiency into Square’s direct communication paths with sellers.

The team works on a range of complex problems including but not limited to product recommendation systems, opportunity ranking, retention modeling and predicting the best time and medium of contact. These models directly empower Square's Sales and Account Management organizations to maximize their ROIs.

Qualifications

You will:

• Drive end to end cross functional machine learning projects: you will build relationships with partner teams, frame problem statements, collect and analyze data, research & build prototypes, and finally productionize your ML solutions by designing and building their full pipelines
• Strengthen your knowledge by using and learning a diverse set of techniques spanning all aspects of machine learning, causal inference, and other forms of statistical modeling to solve important business and product problems
• Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria and develop new ML & data products, features and procedures
• Help build the next generation of data driven and intelligent products at Square

You have:

• 7+ years of industry experience in ML or a PhD in a related field with 4+ years of experience
• Fluency in Python and practical experience in applying CICD best practices
• Excellent breath and depth in ML fundamentals
• Experience in building Ranking and Recommendation Systems
• Experience with cloud-based ML pipelines on GCP or AWS
• Experience launching end-to-end production ML models
• Experience in automating internal business processes via data and ML solutions 
• Experience in stakeholder management and cross-functional collaboration
• The ability to clearly communicate complex concepts to technical and non-technical audiences
• A strong desire to perform and grow in your role

Even better:

• A graduate degree in a technical field relevant to ML (e.g., Computer Science or other STEM fields)
• Experience with designing and evaluating A/B tests for newly launched models
• Experience building scalable ML solutions for user facing or operational teams

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 $202,500 - USD $247,500
Zone B: USD $192,400 - USD $235,200
Zone C: USD $182,300 - USD $222,800
Zone D: USD $172,200 - USD $210,400

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. 

Benefits include the following:

• Healthcare coverage