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Senior Engineering Manager, D&I Analytics

Planet
CompanyPlanet
CategoryEngineering
LocationWashington
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted23 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Welcome to Planet. We believe in using space to help life on Earth. Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one. Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles. As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains. We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world. Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands. About the Role: Planet is looking for a Senior Engineering Manager with experience in guiding and mentoring high-performing engineering teams. In this role, you will lead engineering teams delivering novel machine learning powered products focused on Defense and Intelligence customers. The teams work from research and development, designing algorithms, integrating them into production, and maintaining them via MLOps. For example, the team has developed road and building monitoring products based on our satellite imagery, and built a SuperRes product to enhance our medium resolution imagery. This is a servant leadership role focused on enabling your team members to do their best work in a highly collaborative, distributed environment. This is a full-time, hybrid role which will require you to work from our Washington DC office 3 days per week. Impact You'll Own: Guide your team of machine learning engineers to deliver successful ML products Mentor, coach and unblock your team members, helping them succeed and grow their careers Ensure efficient shipping of product improvements and features  Partner with your product management counterparts to take strategic and tactical decisions Define and implement team processes, including for task planning, code reviews and on-call rotations Establish sound engineering practices to build software and design training & inference pipelines Collaborate across our engineering organization and other cross functional teams to align efforts What You Bring: 6+ years of relevant work experience, with 4+ years of supervisory/leadership experience, with ability to build, retain, and grow diverse, geographically dispersed teams Bachelor’s degree in a relevant field Experience in delivering data-intensive software products at scale Solid understanding of fundamentals in software engineering, statistics and machine learning Success in establishing and evolving operational practices in a software engineering organization Experience owning and maintaining ML models in production  Experience with distributed cloud computing Excellent interpersonal skills, both verbal and written, with the ability to explain complex technical issues accurately to technical and non-technical audiences What Makes You Stand Out: Experience building products using sensor or geospatial data Experience in remote sensing or related fields Ability to obtain security clearance Application Deadline: October 22, 2026 by 11:59p / 23:59 CET (Central European Time) EAR/ITAR Requirements: This position requires access to export-controlled information, and as such, employment (or hiring of a contractor) is contingent upon the candidate’s ability to access
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