Software Engineer - Backend, SI Tooling

Job Description

The SI Tooling team is a central part of Autopilot SI. The systems you build will have a large impact on the entire lifecycle of model development. This includes data processing, data discovery, annotation, and visualization. This also includes tools that help us automate the entire workflows of training, validation, and productionization of our Autopilot neural networks. 

As an Engineer on the SI Tooling team, you bring top-notch software engineering skills and can contribute to our tooling systems immediately. Knowledge of machine learning, computer vision, or neural networks is a plus but not required. That can be learned on the job as you work with our machine learning experts. A strong candidate for the SI Tooling team will either be an excellent software generalist, or someone who is exceptionally strong in either backend or frontend engineering.

Job Responsibilities

• Design and implement large-scale data processing pipelines that handle a diverse set of Autopilot related data such as images, sensor inputs, and human labels
• Design and implement tools, tests, metrics, and dashboards to accelerate the development cycle of our model training
• Work closely with frontend engineers to seamlessly integrate with backend systems
• Work closely with SI researchers to support evolving research projects and implement new production features

Job Requirements

• Strong knowledge of at least one programming language related to data engineering, such as Python or Scala is required
• Experience with scientific computing libraries such as numpy, pandas, or scikit-learn is a plus
• Experience with big data systems such as Spark, Hadoop/MapReduce is a plus
• Experience with cloud computing such AWS EC2/S3/RDS is a plus
• Experience with ElasticSearch or other scalable search systems is a plus
• Experience with real-time data processing is a plus
• Knowledge of machine learning, computer vision, or neural networks is a plus but not required
• Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability