What you'll be doing
- Get paid to work on open-source projects
- Apply cutting-edge best practices and architecture to build Instill AI's products. The topics involve Infrastructure as Code (IaC), microservice, serverless, API-first design, Twelve-Factor Apps, zero-trust network, message queue, etc
- Develop MLOps features and cloud compute platform for processing unstructured data, including data labelling, dataset preparation and versioning, model training and evaluation, experiment tracking, model deployment and monitoring, etc., work with other engineers to integrate ML systems into data pipelines
- Work with product managers, frontend engineers, product designers and other engineers to deliver high-quality, complex ML/AI features on the roadmap
- Reproduce state-of-the-art AI algorithms using deep learning frameworks (e.g., PyTorch, TensorFlow, ONNX and TensorRT) and integrate them with our MLOps workflow
- Deliver high-quality software and documentation
Things we'd love to see
- Significant experience in MLOps, have shipped AI projects before
- Experience with GCP, AWS or other major cloud services
- Experience in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX), Docker, Kubernetes and CI/CD automation
- Be fluent in Python, Go, C/C++, and SQL/NoSQL
- Comfortable working in a fast-paced, agile startup environment, experience in robust and frequent releases
- Excellent communication and document writing skills
- Open-source practices/contributions
- Be customer and data obsessed and take ownership of the details
- Proactive, self-learning, and self-aware
- Intellectual curiosity, always asking "how can we improve?"
- A strong desire to build world-class products