Staff Software Engineer, Machine Learning Data

Quantum computers generate huge amounts of data—and we can use that data to make those very same computers better. We are seeking an enthusiastic Staff Machine Learning Data Engineer who is passionate about machine learning and data engineering. You will help build high quality, scalable, and resilient distributed systems that power our data pipelines. You’ll be responsible for leading the development of the key components of our data and Machine Learning platform, while collaborating with experimental and theoretical physics teams, as well as Machine Learning engineers. Help us use data and Machine Learning to build the world’s best quantum computers!

Responsibilities:

• Lead, design, architect, develop, test, deploy, maintain, and improve our data pipelines and warehousing 
• Ensure the quality of our system through design and code reviews 
• Assist in the career development of others, providing mentorship on advanced technical issues
• Collaborate with an experienced interdisciplinary staff
• Approach problems pragmatically
• Help us continuously improve how we do things

The ideal candidate will have experience leading or contributing to multiple simultaneous product development efforts, projects, and initiatives. You’ll be able to balance technical expertise and savvy with strong business judgment to make great technology choices. You’ll strive for simplicity and demonstrate significant creativity and incisive judgment.

You’d be a good fit with:

• Bachelor’s degree in Computer Science, Mathematics, Physics, Statistics, or equivalent practical experience–untraditional backgrounds are welcome here
• 5+ years experience in software development in one or more general-purpose programming languages (like Go, Rust, or C++)
• 3+ years experience with SQL and NoSQL databases
• Experience designing data models and data warehouses 
• Experience with data processing using traditional and distributed systems (e.g., Airflow, Dataflow, Hadoop).
• Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
• Experience in distributed data processing and Unix or GNU/Linux systems.
• Excellent verbal and written communication skills
• A love of collaborating in an interdisciplinary environment

You’d be a great fit with:

• Master’s degree or PhD in Computer Science, Mathematics, or Statistics, or related scientific field
• 3+ years of experience with one or more of the following technologies
• Kubernetes
• Postgres
• MongoDB
• Airflow
• Solid understanding of deep learning platforms like Keras, Tensor-flow and/or PyTorch
• Experience determining capacity requirements for Machine Learning workloads, and working with partner teams to ensure scalability and maintainability
• Comfort with managing data and Machine Learning workloads in production