Machine Learning Solutions Architect

November 20

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phData

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Spark • Impala • Kafka • Kudu • Scala

201 - 500 employees

Founded 2014

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 $2.5M Seed Round on 2018-03

Description

• As a Solutions Architect on our Machine Learning Engineering team, you are responsible for: • 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

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 of PTO plus 10 Holidays (and other cool perks) • Accelerated learning and professional development through advanced training and certifications