About the RoleWe're seeking an exceptional
AI Software Engineer to develop novel computer vision models for analyzing videos of dogs and cats to diagnose a variety of conditions. This position combines cutting-edge ML research with practical software engineering to create a production-ready diagnostic system that veterinarians can use to improve health outcomes. The roles includes both ML research and standard engineering including writing web servers and deploying models.
Required Skills & Experience- Collaborate with the team to design and implement custom ML architectures optimized for video analysis of canine movement patterns
- Develop full-stack applications to make ML models accessible to veterinary professionals and to work on our video capture platform
- Build and maintain robust backend services and APIs
- Deploy and monitor ML and other systems in production environments
Required Skills & Experience- Ability to read and understand cutting edge research and implement the models they describe.
- 3+ years experience developing and deploying computer vision models
- Strong understanding of deep learning architectures for video processing (CNNs, RNNs, Transformers, ViTs)
- Proficiency in PyTorch
- Experience with back end development using Go, Java, Rust, or strongly typed languages
- Working knowledge of web server technologies and RESTful API design
- Familiarity with cloud infrastructure (AWS/GCP/Azure) and containerization
Preferred Qualifications- Ability to contribute in multiple areas including backend servers, devops, and React/Typescript
- Experience with Go
- MS or PhD in Computer Science, Machine Learning, Math, or related field
- A love of dogs and other furry friends
What You'll Be DoingOne day you might be training a novel neural network architecture on our GPU cluster, the next you could be writing HTTP endpoints for our veterinarian-facing video management application. This role requires someone who is comfortable wearing multiple hats and can transition between ML research and practical software engineering tasks.
The ideal candidate is passionate about applying ML to real-world problems, comfortable with ambiguity, and excited about building technology that improves animal welfare.
