Machine Learning Platform Architect (US)

April 13

Signify

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Signify - An Accumuli Company Signify helps organisations to secure their computer networks$1. .$1

Two-factor authentication • Identity Management • Secure remote access • Strong authentication • Authentication expertise

11 - 50

Description

• Modernize Signifyd’s Machine Learning (ML) Platform to scale for resiliency, performance, and operational excellence working closely with Engineering and Data Science teams across Signifyd’s R&D group. • Create and deliver a technology roadmap focused on advancing our data processing capabilities, which will support the evolution of our real-time data processing and analysis capabilities. • Work alongside ML Engineers, Data Scientists, and other Software Engineers to develop innovative big data processing solutions for scaling our core product for eCommerce fraud prevention. • Take full ownership of significant portions of our data processing products, including collaborating with stakeholders on machine learning models, designing large-scale data processing solutions, creating additional processing facets and mechanisms, and ensuring the support of low-latency, high-quality, high-scale decisioning for Signifyd’s flagship product. • Architect, deploy, and optimize Databricks solutions on AWS, developing scalable data processing solutions to streamline data operations and enhance data solution deployments. • Implement data processing solutions using Spark, Java, Python, Databricks, Tecton, and various AWS services (S3, Redshift, EMR, Athena, Glue). • Mentor and coach fellow engineers on the team, fostering an environment of growth and continuous improvement. • Identify and address gaps in team capabilities and processes to enhance team efficiency and success.

Requirements

• Ideally has over 10 years of experience in data engineering, including at least 5 years of experience as a data or machine learning architect or lead. Have successfully navigated the challenges of working with large-scale data processing systems. • Deep understanding of data processing, comfortable working with multi-terabyte datasets, and skilled in high-scale data ingestion, transformation, and distributed processing, with strong Apache Spark or Databricks experience. • Experience in building low-latency, high-availability data stores for use in real-time or near-real-time data processing with programming languages such as Python, Scala, Java, or JavaScript/TypeScript, as well as data retrieval using SQL and NoSQL. • Hands-on expertise in data technologies with proficiency in technologies such as Spark, Airflow, Databricks, AWS services (SQS, Kinesis, etc.), and Kafka. Understand the trade-offs of various architectural approaches and recommend solutions suited to our needs. • Experience with the latest technologies and trends in Data, ML, and Cloud platforms. • Demonstrable ability to lead and mentor engineers, fostering their growth and development. • You have successfully partnered with Product, Data Engineering, Data Science and Machine Learning teams on strategic data initiatives. • Commitment to quality, you take pride in delivering work that excels in data accuracy, performance and reliability, setting a high standard for the team and the organization.

Benefits

• Discretionary Time Off Policy (Unlimited!) • 401K Match • Stock Options • Annual Performance Bonus or Commissions • Paid Parental Leave (12 weeks) • On-Demand Therapy for all employees & their dependents • Dedicated learning budget through Learnerbly • Health Insurance • Dental Insurance • Vision Insurance • Flexible Spending Account (FSA) • Short Term and Long Term Disability Insurance