Senior Applied ML Engineer, Graph Neural Network, ML Frontiers

Requirements:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 2 years of experience with C++ and Python.
• Experience with machine learning (ML)/AI in a software development environment.

Nice to Haves:

• 5 years of experience with data structures and algorithms.
• 2 years of experience with applied machine learning/machine learning research.
• Experience with one or more neural network frameworks: PyTorch, TensorFlow or Jax.
• Experience with decision trees.

What You'll Be Doing:

• 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.

Perks and Benefits:

• Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent.
• Empowerment culture and bias to action.
• Work on shaping the frontier of enterprise and driving the evolution of advanced models.
• Opportunities for constant exploration, brainstorming with team, research collaborators, and gathering client feedback.
• Mentor and help grow other engineers, research students, and interns.