Software Engineer - Machine Learning

Applied Intuition; Stuttgart; Vor Ort; EUR 60.000 - 100.000; Vollzeit

Zusammenfassung

An innovative company is seeking skilled software engineers to enhance their autonomous vehicle stack through advanced machine learning capabilities. This role offers the opportunity to work on cutting-edge technology in a collaborative environment, focusing on perception, prediction, and planning systems. As part of a dynamic team, you'll contribute to the development of intelligent systems that are transforming the automotive industry. If you're passionate about making autonomous systems a reality and have a strong background in ML, this is the perfect opportunity for you!

Leistungen

Lunch and Dinner Allowances

Annual Fitness Stipend

Annual Learning Stipend

Stock Options

Qualifikationen

• 3+ years of experience in building production software using modern practices.
• Experience with the full development cycle of deep learning models.

Aufgaben

• Design and implement capabilities for perception or planning/prediction systems.
• Leverage existing products to build infrastructure for ML developments.

Kenntnisse

Deep Learning

C++

Python

Machine Learning

Perception Algorithms

Model Optimization

Ausbildung

MSc in Machine Learning

PhD in Machine Learning

Tools

Deep Learning Frameworks

ML Libraries

Jobbeschreibung

About Applied Intuition

Applied Intuition is a vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, we deliver the AI-powered ADAS/AD toolchain, Vehicle OS, and autonomy stack to help customers shorten time to market, build high-quality systems, and create next-generation consumer experiences. Our solutions are trusted by 18 of the top 20 global automakers. We serve the automotive, trucking, construction, mining, agriculture, and defense industries. Our headquarters are in Mountain View, CA, with offices across the US and internationally. Learn more at appliedintuition.com.

Note: We are an in-office company, expecting employees to work primarily from our offices 5 days a week. We offer flexibility for remote work and schedule management, except for EpiSci roles.

About The Role

We seek software engineers with expertise in ML-first perception, prediction, or planning for autonomous vehicles or mobile robots. Your role involves developing key ML capabilities within our autonomous vehicle stack. You will also contribute to our team culture, sharing best practices in the autonomy industry, and help make autonomous systems a reality.

Responsibilities

1. Design and implement capabilities and workflows for perception or planning/prediction systems.
2. Leverage existing Applied Intuition products to build the infrastructure for ML developments.

Qualifications

1. Experience with the full development cycle of deep learning models.
2. Expertise in modeling, input pipelines, evaluation, deployment, and model optimization.
3. 3+ years of experience in building production software using modern practices.
4. Fluency in C++, or Python with intermediate C++ experience.
5. Deep understanding of frameworks or libraries used.
6. Experience with production-level ML and DL perception algorithms for autonomous vehicles.

Preferred Qualifications

1. MSc or PhD in machine learning, perception, prediction, planning, or related fields.
2. Experience building and shipping software frameworks or tools.
3. Experience with driver assistance or autonomous driving systems.
4. Experience evaluating and improving system-in-the-loop model performance.
5. Expertise in algorithms such as non-linear optimization, computational geometry, numerical analysis, or distributed systems.

Benefits and Perks

1. Lunch and dinner allowances.
2. Annual stipends for fitness ($600) and learning ($1,000).
3. Stock options.

Don’t meet every requirement? We encourage you to apply anyway. You might be a great fit for this or other roles.

Applied Intuition is an equal opportunity employer and complies with relevant federal laws on nondiscrimination and affirmative action.