HomeData Science JobsSquare | Hiring | Machine Learning Engineer, Commerce ML | BigDataKB.com |...

Square | Hiring | Machine Learning Engineer, Commerce ML | BigDataKB.com | 08-04-22

Job Location: Atlanta, GA

Company Description

Square builds common business tools in unconventional ways so more people can start, run, and grow their businesses. When Square started, it was difficult and expensive (or just plain impossible) for some businesses to take credit cards. Square made credit card payments possible for all by turning a mobile phone into a credit card reader. Since then Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square.

Job Description

The Commerce ML team applies machine learning to improve the experience of our sellers and help automate the running of their business. In particular, the team focuses on shipping ML-driven features for Square for Retail, in areas such as helping offline sellers get online more easily, setting their catalogs up more quickly, and optimizing their inventory levels. To develop each feature, we pay close attention to four key and interdependent aspects: Design, Modeling, Engineering, and Analytics. Design is concerned about the usefulness and remarkability of the feature, and thus cares about the overall functionality, ease of use, and aesthetics of the experience. Modeling is concerned about the accuracy of the ML model, and thus cares about the training data, the features and performance of the model, and —crucially for a customer-facing product— how the application behaves in the face of the mistakes the model will inevitably make (e.g., false positives, false negatives, lack of predictions above a certain confidence). Engineering in turn is concerned about running the ML model at scale, and thus cares about the latency, throughput, and robustness of the inferencing service. Finally, Analytics is concerned about the adoption of the feature, and thus cares about the instrumentation to capture detailed usage and acceptance rate, the definition of success metrics and dashboards, and the collection of feedback in a manner that the ML model can learn from, and thus keep improving over time.

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If developing customer-facing ML-driven product features fascinates you, we are looking for an ML modeler to join the team and help deliver the future of Square for Retail!

You will…

  • Play a key role in developing ML-driven product features that help millions of Sellers worldwide

  • - Advertisement -

    Develop data pipelines, engineer features, and train ML models for NLP, computer vision, and other use cases

  • Build and maintain low-latency, high-RPS ML services

  • Work cross-collaboratively with data scientists, product managers, and designers to iterate on and define product functionality and UX design

  • Partner closely with platform and product teams to review engineering designs and provide architectural guidance

Qualifications


You have…

  • Excellent understanding of ML modeling techniques, from “classic” statistical classifiers to “modern” deep learning and transformer approaches

  • Experience applying ML to solving complex business problems

  • Good command of engineering fundamentals

  • Experience with NLP and/or computer vision use cases a plus

  • Motivation to build beautiful, intuitive products

  • Innate curiosity, and a desire to learn and teach

  • Empathy for your customers and colleagues

  • Eagerness to share your own ideas, and openness to those of others


Languages and tech frameworks we use (and teach)…

  • PyTorch, TensorFlow, Keras; scikit-learn, spaCy, Hugging Face; Spark

  • Python, Java, JavaScript, Go, Ruby

  • MySQL, Redis, Kafka, Elasticsearch, PostgreSQL, Cassandra, Memcached

  • AWS, GCP

Additional Information

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page.

Additionally, we consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.


Perks

We want you to be well and thrive. Our global benefits package includes:

  • Healthcare coverage
  • Retirement Plans
  • Employee Stock Purchase Program
  • Wellness perks
  • Paid parental leave
  • Paid time off
  • Learning and Development resources


Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.

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