Controls Systems Engineer, Machine Learning, Platforms

Minimum qualifications:

• Bachelor's degree in Engineering, Science, a related field, or equivalent practical experience.
• 5 years of experience designing and implementing controls systems and dynamic modeling.
• 5 years of experience with Machine Learning and construction of algorithms.
• Experience with programming in C, Python, MATLAB, or Shell.
• Experience with software development or prototyping within a business or enterprise setting.

Preferred qualifications:

• PhD in Engineering, Science, or a related field.
• Experience with modeling/statistical software such as TensorFlow, Simulink, R, or MATLAB Machine Learning Toolbox.
• Experience with digital signal processing and time-series analysis. Experience with optimization, Linear Programming, and Convex Optimization.
• Experience with dynamic system analysis, feedback control systems, and optimal control.
• Experience with developing AI/ML prototypes and conducting full-cycle modeling experiments within a business or enterprise setting.
• Familiarity with modern software development practices (e.g., version control, clean code).

About the job

Our thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians.

With your technical expertise, you ensure compliance with codes and standards, develop infrastructure improvements and serve as an expert in your specialty (e.g., cooling, electrical).

The Data Center Engineering team takes the physical design of our data centers into the future.

In this role, you will take on complex topics, optimize for efficiencies, and always seek ways to improve. You will also generate ideas, communicate recommendations to executives and drive implementation alongside facilities technicians.The US base salary range for this full-time position is $144,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

In this role, you will take on complex topics, optimize for efficiencies, and always seek ways to improve. You will also generate ideas, communicate recommendations to executives and drive implementation alongside facilities technicians.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Conduct empirical statistical analysis and modeling of physical variables in data center systems.
  
• Design, implement, and validate control systems supporting service-level objectives. Research and develop new methods and algorithms to optimize data center efficiency and performance.
  
• Analyze and recommend approaches to manage dynamics of the electromechanical systems and their interactions within a data center.
  
• Collaborate across engineering teams to implement new algorithms, strategies, and processes.
  
• Develop large-scale Machine Learning algorithms for pattern recognition and Bayesian and non-linear systems.