Machine Learning Infrastructure Engineer
Skydio is the leading US drone manufacturer and world leader in autonomous flight, the key technology for the future of drones and aerial transportation. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, and operational excellence to empower a broader, more diverse audience of drone users - from action sports enthusiasts to first responders.
About the role:
As a member of the Autonomy team at Skydio, you will be responsible for building systems to accelerate the development and deployment of deep learning models built by our autonomy research engineers. Our models solve various semantic and geometric tasks and are trained on massive datasets to make our drones the smartest flying robots in the world.
How you'll make an impact:
- Build elastic data pipelines that process billions of pixels per day;
- Build elastic training pipelines;
- Work with our research engineers to automate aspects of our pipeline and deploy research models in production;
- Work with our Infrastructure team to build core abstractions and create standards and best practices for building our teams.
What makes you a good fit:
- Solid background in algorithms, data structures, and object-oriented programming.
- Experience in building scalable and fault-tolerant distributed systems that process large volumes of data.
- Degree in computer science or related field.
- Knowledge of deep learning and computer vision.
- Experience or interest in working with game engines.
Nice to haves:
- Experience working with a cloud technology stack (eg. AWS or GCP).
- Experience building machine learning training pipelines or inference services in a production setting.
- Experience building, deploying, and monitoring complex microservice architectures.
- Experience with machine learning frameworks and libraries (PyTorch, Tensorflow, Kubeflow).
- Experience with big data tools (SPark, Flink, Hadoop) and building ETL and streaming pipelines.
- Experience with Python, Docker, Kubernetes, and Infrastructure as code (eg. Terraform).
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At Skydio we believe that diversity drives innovation. We have created a multi-disciplinary environment that embraces the power of diverse perspectives to create elegant solutions for complex problems. We are committed to growing our network of people, programs, and resources to nurture an inclusive culture.
As such, we do not make hiring or other employment-related decisions on the basis of an applicant or employee’s race, color, ethnicity, national origin, citizenship, sex (including pregnancy, childbirth, breastfeeding and related medical conditions), pregnancy, gender, gender identity or expression, age, religion, disability status, sexual orientation, marital status, medical condition, generic information or characteristics, veteran, military or family status, or other classifications protected by applicable federal, state or local anti-discrimination laws.
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