Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Staff Machine Learning Engineer at Planet
I am a Staff Machine Learning Engineer with Planet, applying deep learning to geospatial AI problems. Planet has a fleet of Low Earth Orbit cubesats that image the land mass of the Earth daily to monitor changes and pinpoint trends. At Planet I've done everything from detecting new roads and buildings appearing in protected areas of the Brazilian Amazon to helping figure out how to put machine learning GPUs into space to applying cutting edge advancements in AI to Earth Observation problems. I have a decade and a half experience as a software engineer across such companies as Google & Dropbox, startups, and the open source world. I am a Machine Learning Advisor to the Frontier Development Lab, helping research teams apply deep learning to Earth and space science and space exploration. I was a Machine Learning Engineer at Dropbox, doing industrial R&D to ship deep learning-powered products to millions of users and across billions of files. I've worn many hats in my career, whether as a tech lead, a product engineer, a startup founder, or a full stack software engineer. I have a long tradition of untraditional, cross-disciplinary innovation across fields. Earlier work includes having started Coworking, which grew into an international grassroots movement to establish a new kind of workspace for the self-employed, with more than 15,000 coworking spaces now open globally. At a startup named Inkling I founded Inkling Habitat, re-imagining interactive digital textbooks for higher education and how they are published by adopting ideas from computer science — Inkling Habitat turned into a multi-million dollar business that was adopted by the world’s major educational publishers, including Pearson & Elsevier. At Google I helped the web blossom into a true application deployment platform through efforts like HTML5. Finally, I worked with Douglas Engelbart, the inventor of
Columbia University
B.A., Computer Science
N/A – Present
Planet
Staff Machine Learning Engineer
January 1, 2020 – Present
San Francisco Bay Area
Frontier Development Lab (FDL)
Machine Learning Research Advisor
January 1, 2019 – Present
Dropbox
Full Stack Senior Machine Learning Engineer, Machine Learning Team
January 1, 2014 – January 1, 2018
San Francisco
Inkling
Senior Software Engineer/Tech Lead
January 1, 2010 – January 1, 2014
San Francisco Bay Area
Software Engineer/Developer Advocate
January 1, 2007 – January 1, 2010
Various
Earlier Selected Roles/Projects
January 1, 2004 – January 1, 2007
San Francisco Bay Area
Cultural Fit Analysis
The candidate's diverse background, including inventing coworking, working with Douglas Engelbart, and contributing to open-source toolkits, suggests a highly innovative, collaborative, and pioneering spirit. Their experience across various companies (Google, Dropbox, Planet) and roles (Software Engineer, Tech Lead, Machine Learning Engineer, Research Advisor) demonstrates adaptability and a broad interest in technology. The emphasis on user empathy, product focus, and rapid testing aligns well with modern agile development cultures. However, the recent deep specialization in Machine Learning might pose a cultural fit challenge for a pure Frontend Developer role, as their primary passion and recent contributions appear to be in ML/AI. While they have strong frontend foundations, their career trajectory has moved away from it.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentorship, and strategic thinking capabilities, particularly in setting AI strategy and leading engineering teams. Their involvement in founding Inkling Habitat and creating a strong engineering culture indicates a focus on best practices, mentorship, and agile development. The candidate's history of inventing and evangelizing coworking, as well as their work as a Developer Advocate at Google, suggests strong communication and community-building skills. Their volunteer work as a research advisor at FDL also points to a collaborative and knowledge-sharing mindset. However, the target role is 'Frontend Developer', and while the candidate has significant frontend experience, their recent roles have been heavily focused on Machine Learning, which might indicate a shift in primary interest or a need to re-align with core frontend development practices.