Machine Learning Software Engineer

We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.

We are looking for software engineers with expertise in ML-first perception, prediction or planning for autonomous vehicles or mobile robots. Your contributions will focus on building out key ML capabilities of an autonomous vehicle stack. 

In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the autonomy industry. We move fast and 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 Intuition is the place for you!

• Design and implement capabilities and workflows for cutting-edge real-world perception or planning/prediction systems
• Leverage established products at Applied Intuition to build the software and infrastructure foundation for our ML developments

• Experience with the end-to-end development cycle of deep learning models 
• Expertise in subdomains such as modeling, input pipelines, evaluation, deployment, and model optimization
• 3+ years of experience building production software using modern software practices
• Fluency in C++, or fluency in Python with intermediate experience in C++
• Deep understanding of the concepts and methods behind any frameworks or libraries that they worked with
• Experience working with production level ML and DL perception algorithms for autonomous vehicles

• MSc or PhD in machine learning, ideally applied to perception, prediction,planning or closely related field
• Experience building and shipping software frameworks or tools
• Experience with driver assistance or autonomous driving systems
• Experience in evaluating and improving system-in-the-loop model performance
• Deep hands-on expertise in relevant algorithms or methods, such as non-linear optimization, computational geometry, numerical analysis, or distributed systems