Senior Software Engineer, Back End

The Engineering team is responsible for building out the platforms, API’s, services, workflows, and logical architectures for bringing this vision to life.  We are creating a platform fundamentally driven by AI, which scales to a massive trove of data, and a diverse customer base; it is a complex system that will stretch engineering in many directions.  You’ll work closely with our Data Scientists on projects to analyze and observe world-scale datasets, write code that can scale to produce never before seen insights, and construct APIs to deliver our product vision.

Responsibilities

• Ingest product requirements, define technical requirements, and design practical, iterative technology designs that achieve the goal while fitting into our overall technical and product roadmaps
• Be responsible for technical output of developers – creating, and enforcing standards, patterns and practices for effective development.
• Personally develop and deploy services creating and supporting our overall architecture -- Atlas Knowledge Graph API, Atlas Edits and Change Service, Entity Resolution Service, Trusted Network Services, Trusted Shipment Services, etc.
• Build and maintain distributed machine learning pipelines
• Analyze and propose technical solutions to invent, enable, and enhance our product offerings
• Be responsible for automating, testing, and deploying your work
• Collaborate with fellow engineers and data scientists across the organization

 About You

• BS or MS degree in Computer Science, Data Science, or equivalent experience
• You have 5+ years of real-world professional experience writing back end or data-driven software in demanding environments
• Self-starter who wants to get things done
• You care deeply about engineering excellence, clean code, and knowledge-sharing
• You have strong written and verbal communication skills

   Nice to have, but not required

• Experience with Python Machine Learning toolsets (Scikit-learn, Numpy, Pandas, Dedupe)
• Experience with container technologies like Docker and Kubernetes
• Working knowledge of cloud services like AWS, Azure, or GCP

 Technologies we love

• Languages: Python, Spark
• Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS
• Datastores: Databricks, Elasticsearch, Postgres