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Research Engineer

Salary

$125k - $242k

Min Experience

0 years

Location

Mountain View, California, United States

JobType

full-time

About the job

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About the role

The AI Research Team at Applied Intuition conducts world-class research for autonomous systems and closed-loop simulation, and creates scalable autonomy stacks from prototype towards mass production in a data-driven fashion. You will have access to driving data exploding from millions of miles with various scenarios from a diverse set of sensors to develop industry-leading models and techniques at scale. Improvements deployed to our system can immediately help our customers with their autonomy programs. In addition to your research contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the nascent autonomy industry. We move fast and we focus on excellence, for our products and for our business. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied is the place for you! At Applied Intuition, you will: Design and implement one of the following areas: Next-generation, data-driven ADAS stack with an end-to-end structure covering conventional perception, mapping, prediction and planning modules towards industry-leading performance Closed-loop simulation with sensory and behavior generation in a data-driven paradigm Conduct research for the differentiable stack on its architecture design, robustness and safety, language modality incorporation, close-loop simulation and its utilization Work closely with our ADAS stack engineering team to test and deploy the implemented end-to-end algorithms for mass production vehicles, or our simulation team to deploy data-driven generation algorithms for highly efficient and automated tools Work closely with research scientists and intern students in the AI Research team towards high quality research publications We’re looking for someone who has: Deep hands-on experience with one of the following aspects: End-to-end (perception to planning) autonomy stack Multi-view perception based on Transformer with BEV representation and temporal fusion, based on real-world data with real vehicle tests 3D reconstruction, and diffusion model for sensory generation Closed-loop behavior generation with data-driven methods Passion for next-generation, scalable autonomy with data-driven, differentiable paradigm and large data/model deployment for real-world autonomous systems Nice to have: MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field Hands-on experience of imitation/reinforcement learning, behavior prediction, and closed-loop simulation Experience with training with large-scale data and ML models Passion for or experiences with applications of language modality in driving Experience building and shipping software frameworks or tools that are used by others than the authors of the framework Autonomy is one of the leading technological advances of this century that will come to impact our lives. The work you’ll do at Applied will meaningfully accelerate the efforts of the top autonomy teams in the world. At Applied, you will have a unique perspective on the development of cutting edge technology while working with major players across the industry and the globe.

About the company

Applied Intuition is a vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the AI-powered ADAS/AD toolchain, vehicle platform, and autonomy stack to help customers shorten time to market, build high-quality systems, and create next-generation consumer experiences. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in Ann Arbor and Detroit, MI, Washington, D.C., Stuttgart, Munich, Stockholm, Seoul, and Tokyo.

Skills

machine learning
computer vision
autonomy
robotics
data-driven methods