For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.
Job Description/ Responsibilities:
Required Skills:
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
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Develop and own deep learning R&D for computer vision, designing and implementing algorithms, improving model performance, and applying advances in AI to 2D and 3D vision technologies.
Build and improve production machine learning systems, developing scalable data pipelines, deep learning and time-series models, agentic workflows, and monitoring processes for model performance.
Develop and scale generative world models and synthetic video pipelines, integrating training-ready data into autonomous-driving models and measuring its impact on evaluation and on-road performance.
Build end-to-end machine learning systems for real-time fraud detection, from large-scale feature engineering and model training to low-latency prediction serving across distributed infrastructure.
Build and optimize the ML platform, tools, and pipelines that help teams develop, train, evaluate, and deploy perception, prediction, and planning models for AD/ADAS systems.
