Optimization Research Engineer - Power Grid AI

Google; Town of Montana (WI); On-site; USD 147,000 - 210,000; Full time

Benefits offered by this job

Bonus 15% target

Equity

Benefits

Job summary

Google DeepMind is seeking an Optimization Research Engineer to tackle large-scale optimization challenges and advance AI across real-world datasets. You will engage in research-driven engineering, prototype architectures, and collaborate with cross-functional teams to deploy ideas broadly.

The role emphasizes building ML models on novel data, integrating optimization methods with ML workflows, and contributing to safety and ethics while pushing the boundaries of AI for global impact.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years working with large-scale optimization models.
• 2 years of experience with solvers and problem types, including integer, nonlinear, and stochastic programs.
• Experience with machine learning, TensorFlow, and software engineering.
• Experience building machine learning models on novel, real datasets.

Responsibilities

• Solve challenging optimization problems for power grids.
• Write reports and presentations.

Skills

Machine learning

TensorFlow

Software engineering

Optimization modeling

Education

Bachelor's degree or equivalent

Job description

Google DeepMind is seeking an Optimization Research Engineer to tackle large-scale optimization challenges and advance AI across real-world datasets. You will engage in research-driven engineering, prototype architectures, and collaborate with cross-functional teams to deploy ideas broadly.

The role emphasizes building ML models on novel data, integrating optimization methods with ML workflows, and contributing to safety and ethics while pushing the boundaries of AI for global impact.