Job Requirements:<\/p>\n\n\n\n
In this role, you’ll:<\/strong> Job Requirements: In this role, you’ll:\u2022 Develop and run large scale optimization and estimation routines. Replay and simulate using existing log data to characterize performance, tune parameters, identify failures and provide performance guarantees\u2022 Integrate sensors into pose estimation and inertial navigation algorithms for deployment on the self driving car. Examples include Kalman filters, EKF, UKF, […]<\/p>\n","protected":false},"author":1,"template":"","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":""},"_links":{"self":[{"href":"https:\/\/otaxio.com\/careers\/wp-json\/wp\/v2\/awsm_job_openings\/22488"}],"collection":[{"href":"https:\/\/otaxio.com\/careers\/wp-json\/wp\/v2\/awsm_job_openings"}],"about":[{"href":"https:\/\/otaxio.com\/careers\/wp-json\/wp\/v2\/types\/awsm_job_openings"}],"author":[{"embeddable":true,"href":"https:\/\/otaxio.com\/careers\/wp-json\/wp\/v2\/users\/1"}],"wp:attachment":[{"href":"https:\/\/otaxio.com\/careers\/wp-json\/wp\/v2\/media?parent=22488"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u2022 Develop and run large scale optimization and estimation routines. Replay and simulate using existing log data to characterize performance, tune parameters, identify failures and provide performance guarantees
\u2022 Integrate sensors into pose estimation and inertial navigation algorithms for deployment on the self driving car. Examples include Kalman filters, EKF, UKF, particle filters, etc.
\u2022 Investigate sensor and filter performance issues. Debug through replay, simulation, residual-analysis and on-car testing
At a minimum we\u2019d like you to have:
\u2022 PhD or M.S. degree with equivalent experience in fields such as estimation, optimization, statistics, modeling, dynamics, control, etc.
\u2022 5+ years of C++ programming experience
It\u2019s preferred if you have:
\u2022 Domain knowledge and implementation experience with Kalman filtering, inertial sensors, and sensor fusion. Real world experience with system integration and deployment
\u2022 Experience with real-time robot\/vehicle\/drone positioning and localization
\u2022 System dynamics and kinematics modeling for ground vehicles<\/p>\n","protected":false},"excerpt":{"rendered":"