We are looking for an experienced and motivated engineer with experience in backend web services and ML infrastructure to help Hume AI empower developers around the world. In this role you will help us integrate cutting edge AI models into services and toolkits for researchers and developers. You will work closely with research scientists and frontend engineers to build new capabilities into the Hume platform, and you will have the opportunity to take part in a wide range of engineering initiatives across the ML lifecycle, including model training, evaluation, and deployment at scale.

Requirements

• Expertise in the Python ecosystem and popular ML libraries and tools (e.g. PyTorch, JAX, TensorFlow, XGBoost, sklearn, pandas, numpy)
• Understanding of core ML concepts including model architecture, training, and evaluation
• Expertise working with storage and compute on a cloud platform (e.g.Google Cloud, AWS)
• Deep understanding of modern deployment strategies utilizing cloud technologies. (e.g. blue/green, canary deployments, etc)
• Experience using service deployment tooling (e.g. Kubernetes, Docker, Argo)
• Excellent communication and collaboration skills

Bonus

• Experience writing backend services in multiple languages (e.g. Kotlin, Go, Rust, Java, C++)
• Knowledge of one or several MLOps platforms for experiment tracking or model training (e.g. Sagemaker, Vertex, Weights and Biases)
• Familiarity with distributed training and compute tools like Dask, Ray, and Spark
• Experience working at the intersection of machine learning research and engineering