Job summary
Key job responsibilities
As a Software Development Engineer in DSI, you will:
• Work in a cross-functional team of product managers, Software and Data Engineers, and Scientists to build causal machine learning systems.
• Build data processing systems on AWS technologies (e.g., S3, EC2, EMR) and Apache Spark to process TBs of data.
• Apply MLOps principles to facilitate rapid scientific innovation and experimentation.
• Develop and scale machine learning applications (e.g., Deep Learning) in Python on massive datasets
• Learn about the science of causal inference and lead the implementation of new concepts in production
• Engineer systems to meet strict SLAs for routine reports, self-service requests, and automated systems.
• Engage with customers and partner teams to improve product scope and usability.

· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
· 2+ years of non-internship professional software development experience

Here are some things that we want to see, though none is independently a requirement:
• Experience building machine learning applications
• Knowledge of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Ability to take a project from scoping requirements through actual launch of the project
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Experience with large data sets (>1TB); Spark and MapReduce a strong plus.
• Experience with MLOps infrastructure including designing and building systems for model training pipelines and high performance, low latency inference services.
• Experience working with high volume, low-latency (>100K requests per second, <100ms latency) web services a strong plus.