Machine Learning Solutions Architect

Role Overview

• Designing and implementing data solutions best suited to deliver on our customer needs — from model inference, retraining, monitoring, and beyond — across an evolving technical stack.
• Providing thought leadership by recommending the technologies and solution design for a given use case, from the application layer to infrastructure; and they have the team leadership and coding skills (e.g. Python, Java, and Scala) to build and operate in production; and to help ensure performance, security, scalability, and robust data integration.
• Design and create environments for data scientists to build models and manipulate data
• Work within customer systems to extract data and place it within an analytical environment
• Learn and understand customer technology environments and systems
• Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop
• Demonstrate the business value of data by working with data scientists to manipulate and transform data into actionable insights
• Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models
• Partner with data scientists to ensure solution deployability—at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle
• Create operational testing strategies, validate and test the model in QA, and implementation, testing, and deployment
• Ensure the quality of the delivered product

Requirements

• At least 6 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
• 4-year Bachelor's degree in Computer Science or a related field
• Experience deploying machine learning models in a production setting
• Expertise in Python, Scala, Java, or another modern programming language
• The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets
• Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries
• Hands-on experience in one or more big data ecosystem products/languages such as Spark, Snowflake, Databricks, etc.
• Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)
• Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), and storage systems (e.g., AWS, Databricks, Cloudera)
• Production experience in core data technologies (e.g. Spark, HDFS, Snowflake, Databricks, Redshift, & Amazon EMR)
• Development of APIs and web server applications (e.g. Flask, Django, Spring)
• Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment
• Excellent communication and presentation skills; previous experience working with internal or external customers.

Tech Stack

• Amazon Redshift
• AWS
• Cloud
• Django
• Flask
• HDFS
• Java
• Kafka
• Linux
• MySQL
• Oracle
• Python
• RDBMS
• Scala
• Spark
• Spring
• SQL

Benefits

• Remote-First Work Environment
• Casual, award-winning small-business work environment
• Collaborative culture that prizes autonomy, creativity, and transparency
• Competitive comp, excellent benefits, 4 weeks PTO plus 10 Holidays (and other cool perks)
• Accelerated learning and professional development through advanced training and certifications