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The Research Engineer will design and implement data-driven ADAS stacks, conduct research on architecture design and safety, collaborate with engineering teams for deployment, and engage with research scientists for high-quality publications.
The Research Scientist will conduct advanced research in AI and autonomous systems, focusing on scalable autonomy stacks and closed-loop simulations. The role involves collaboration with peers and engineers to develop algorithms and contribute to industry-leading publications. Candidates should have a strong research background and be passionate about deploying models in real-world autonomous systems.
The ML Perception Software Engineer will design and implement perception capabilities for autonomous vehicles, focusing on machine learning and computer vision techniques. They will collaborate with sensor simulation and infrastructure teams to enhance simulation models and provide enterprise software solutions for engineering teams.
As a Leadership Sourcer at Applied Intuition, you will identify and engage top leadership talent across various functions, screen candidates, collaborate with leadership, and manage recruiting-related projects to enhance the hiring process.
The Technical Writer will create and maintain product documentation, including tutorials and user manuals, by collaborating closely with engineers and product specialists. Responsibilities include establishing documentation processes, meeting customer needs for documentation, and contributing to technical blog posts.
In this role, you will design and implement comprehensive testing frameworks for cutting-edge autonomy solutions. Responsibilities include creating automated test scripts, analyzing test results, and collaborating with engineers and product managers. You'll prioritize test plans and sign-off on test results to improve testing requirements.
The ML Engineering Manager at Applied Intuition will lead a team of machine learning and software engineers to develop advanced ML systems, focusing on simulation for autonomy programs. Responsibilities include setting the technical direction, managing software quality, and collaborating with customers to solve challenges in applied machine learning.
Responsible for developing and expanding product offerings on Windows and Linux, leading efforts with deep knowledge of native APIs and build systems, and mentoring junior engineers. Collaborate with domain experts and contribute to engineering solutions.
The System Safety Engineer will define and manage safety requirements for autonomy software and hardware in automotive systems. Responsibilities include deriving safety requirements according to various ISO standards, contributing to safety case development, and collaborating with cross-functional teams to ensure safety integration throughout the product lifecycle.
The Senior ML Perception Engineer role involves designing and implementing multi-sensor perception models to support the development of scalable offboard systems for self-driving cars, collaborating with teams to ensure effective end-to-end solutions, and contributing to improvements that enhance customer autonomy programs.
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