Machine Learning Infrastructure Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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. 

Nice to haves:

• Experience working with game engines. 
• 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). 

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.