Software Engineer - Machine Learning Infrastructure - Surreal Research

Welcome to the Surreal team in Reality Labs Research! Our team is dedicated to advancing the state-of-the-art in computer vision, machine perception, machine learning, and artificial intelligence. We are a diverse group of researchers, engineers, and technologists who work together to develop cutting-edge technology that pushes the boundaries of what is possible. One of our flagship projects is the Aria device, which is a wearable device that enables us to collect data about the world around us. With Aria, we can gather information about the environment, people, and objects, and use this data to develop new algorithms and models for machine perception and advance artificial intelligence research. As a member of our team, you will have the opportunity to work on exciting projects that have the potential to make a real impact on the world. Whether you are interested in developing new algorithms for object recognition, creating novel approaches to scene understanding, or exploring the intersection of machine learning and robotics, there is something here for everyone. We are looking for talented individuals who are passionate about computer vision, machine perception, machine learning, and artificial intelligence. If you are excited about the prospect of working on cutting-edge technology and making a difference in the world, then we encourage you to apply to join our team.

Software Engineer - Machine Learning Infrastructure - Surreal Research Responsibilities

• Design, develop and maintain machine learning infrastructure to support the training and deployment of machine learning models.


• Collaborate with research scientists and research engineers to build end-to-end machine learning pipelines and support infrastructure that can be deployed in a production environment.


• Optimize machine learning infrastructure for performance, scalability, and reliability.


• Develop and maintain tools and libraries to support the machine learning workflow.


• Ensure the security and privacy of machine learning data and models.


• Stay up-to-date with the latest developments in machine learning infrastructure and related technologies.


• Collaborate with cross-functional teams to identify opportunities for improvement and innovation.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.


• 3+ years of programming experience in either C, C++, Python, Java, C# or other relevant coding languages


• 3+ years relevant experience building large-scale infrastructure applications or similar experience


• Experience with machine learning infrastructure, including tools and frameworks for building, training, and deploying machine learning models at scale.


• Knowledge of distributed computing and parallel processing techniques.


• Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.


• Experience building and shipping high quality work and achieving high reliability


• Experience improving stability through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes


• Knowledge of cloud platforms such as AWS, GCP, and Azure

Preferred Qualifications

• Experience developing and contributing to Open Source projects and libraries.


• Familiarity with secure bulk data storage systems, and experience working with large-scale datasets.


• Experience with containerization technologies such as Docker and Kubernetes.


• Knowledge of real-time systems and experience developing applications that require low-latency processing and high throughput.

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