Control Systems Engineer
Taara
Location
Sunnyvale, CA
Employment Type
Full time
Location Type
Hybrid
Department
Engineering
About the Team:
Born at X, Google's Moonshot Factory, Taara is on a mission to connect billions of people lacking abundant and affordable internet today by pioneering the way we use light to deliver faster, cheaper, more reliable connectivity. Lead the charge in bringing our groundbreaking wireless optical communication and photonics chip technologies to the world. Drive our growth story as we scale innovative solutions across the world. Join us to light the way for bridging the digital divide and illuminating the future.
Role Overview:
Taara is seeking a Control Systems Engineer responsible to define and implement the next generation pointing and tracking algorithms for wireless optical communication systems. The position seeks highly-motivated individuals that enjoy working in a small dynamic team environment, with a passion for solving challenging problems that can lead to high-impact advances in technology.
About the Role:
Develop next-generation control algorithms for high-bandwidth, high-accuracy tracking systems.
Develop and implement active and passive vibration control strategies to reject external disturbances.
Prototype solutions through algorithmic research, simulation, hardware implementation, and field validation.
Define the hardware and software architecture and perform the sensor and actuator selection and characterization.
Design and conduct field experiments to rigorously test and validate system performance against key metrics in real-world environmental conditions
Work closely with various teams to balance short-term and long-term priorities and tasks to maximize project learnings.
Stay up-to-date on the latest control system technologies and trends.
Own the design of a controller architecture for a unique application that will be implemented on thousands of autonomous products in the field.
What you should have:
Master’s degree in a STEM field such as Robotics, CS, Physics, Mechanical Engineering, Aerospace Engineering, or related field, with a strong foundation in controls.
Completed coursework in control systems theory, convex optimization, calculus / differential equations, linear algebra, or their equivalents.
3+ years of experience implementing control systems using a variety of hardware: sensors, actuators, microprocessors, general analog or digital electronics.
Hands-on experience developing dynamic models and simulations for electro-mechanical systems.
Experience with control systems research, or guiding applications such as: motion control, robotics, optimization, signal processing or time-series analysis.
Experience with one or more general purpose programming languages, including but not limited to: Python, C/C++, Golang, Matlab, Simulink.
Excellent problem-solving and analytical skills.
Strong communication and teamwork skills.
Ability to work in the Sunnyvale office at least 3 days per week.
It would be great if you also had these:
Ph.D in a STEM field such as Robotics, CS, Physics, Mechanical Engineering, Aerospace Engineering, or related field, with an advanced foundation in controls.
Experience with advanced control theory techniques such as advanced/nonlinear control systems theory, optimal control theory, robust control theory, online optimization, multi-system coupling, linear and nonlinear stability analysis, and stochastic control techniques.
Experience with state estimation techniques, such as Kalman filtering (EKF, UKF) for sensor fusion and noise rejection.
Experience with implementing control systems using a variety of hardware: sensors, actuators, microprocessors, high-speed digital electronics.
Real-world experience with control systems: algorithmic trade studies to determine best path forward; deployed in hardware; creating detailed simulations; conducting analytical system analysis.
Deep understanding of practical (real-world implementation) differences between linear and nonlinear control systems, their implications, and understanding techniques for optimizing performance in either.
Experience with reinforcement learning (RL) to model complex nonlinear systems, optimize the control system performance, enhance decision-making and predict maintenance.
The US base salary range for this full-time position is $160,000 - $210,000 + 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 location during the hiring process.
