Develop feature development (design, coding, doc writing, and maintenance), research exploration (reading papers, benchmarking, and possibly going/submitting to ML conferences), collaborate with clients (from small consultation to large engagements) and partners (e.g., Google Research).
Implement a distributed graph sampling algorithm (without Flume), benchmark a newly published graph convolution layer in JAX, or develop an interactive Colab component to analyze a trained model.
Participate in brainstorming and help define future applied research, engineering, and product roadmap priorities.
Focus on Graph Neural Networks within Graph Flow, collaborate with the remainder of the ML Frontiers teamwhile working on LLM agents and decision forests.

Senior Applied ML Engineer, Graph Neural Network, ML Frontiers

Job Description