Aumovio
Automotive
ArtificialIntelligenceIntern
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“Artificial Intelligence Intern at Aumovio. Skills: Artificial Intelligence, Embedded AI, Computer Vision, Generative AI, NLP, Python, Deep Learning frameworks. Develop efficient AI models for deployment in resource-constrained automotive environments. Explore and implement optimization methodologies for AI models intended for embedded devices and edge platforms”
What You'll Achieve.
Contribute to AI solutions that support smarter, safer, and more autonomous vehicles
Industry & Context.
Real-world AI deployment challenges
What They're Looking For.
Must Have
Currently pursuing a bachelor’s or master’s degree in programmes such as: Computer Science, Artificial Intelligence / Machine Learning, Computer / Electrical Engineering, or a related field, Proficiency in Python, Hands-on experience with machine learning projects (personal, academic, or open-source), Ability to clearly document findings and present results to team members, verbal and written communication skills, A collaborative mindset, openness to learning from experienced professionals, and the ability to work effectively in team-based projects, Genuine enthusiasm for artificial intelligence and machine learning, with a desire to stay updated on the latest advancements in the field
Nice to Have
Coursework in AI, Deep Learning, or Computer Vision is highly recommended, Familiarity with deep learning frameworks like PyTorch, TensorFlow, or scikit-learn, Willingness to learn and explore new AI concepts, Hands-on experience with compiling and deploying code onto hardware targets such as SBCs like a Raspberry Pi, or microcontrollers
What You'll Do.
Develop efficient AI models for deployment in resource-constrained automotive environments
Explore and implement optimization methodologies for AI models intended for embedded devices and edge platforms
and improve AI models for real-world automotive use cases
Investigate methods for deploying lightweight Small Language Models on edge devices
Evaluate the performance
and deployment feasibility of developed AI models
Research and analyze the latest AI advancements
and improve state-of-the-art AI methods
or use existing AI models for resource-constrained environments
Leverage cloud-based model development pipelines
Apply model optimization techniques
Explore and implement methods for deploying lightweight Small Language Models on the edge
Contribute to AI-powered autonomous driving and safety system applications
and test AI models or related software on embedded hardware platforms
Conduct experiments and evaluations
How You'll Work.
Team & Collaboration
Collaborate with AI experts in Singapore and across the globe; Present results to team members; Work effectively in team-based projects; Communicate project outcomes to team members and stakeholders
Communication Scope
Clearly document findings; Present results; Verbal communication skills; Written communication skills; Prepare and deliver presentations
Full Job Description
Since its spin-off in September 2025 AUMOVIO continues the business of the former Continental group sector Automotive as an independent company. The technology and electronics company offers a wide-ranging portfolio that makes mobility safe, exciting, connected, and autonomous. This includes sensor solutions, displays, braking and comfort systems as well as comprehensive expertise in software, architecture platforms, and assistance systems for software-defined vehicles. In the fiscal year 2024 the business areas, which now belong to AUMOVIO, generated sales of 19.6 billion Euro. The company is headquartered in Frankfurt, Germany and has about 87.000 employees in more than 100 locations worldwide. This internship focuses on Developing Efficient AI Models in Resource-Constrained Environments, with exciting applications such as: • Autonomous Driving & Safety Systems – Contribute to AI-powered self-driving, assisted parking, and advanced safety features like emergency braking and fallback systems. • LLM-based Interactive Cockpit Systems – Develop methods and applications to deploy lightweight Small Language Models on the edge for use-cases such as car cabin controls, or automotive conversational assistants. Primary Goals: • Develop efficient AI models for deployment in resource-constrained automotive environments. • Explore and implement optimization methodologies for AI models intended for embedded devices and edge platforms. • Build, modify, benchmark, and improve AI models for real-world automotive use cases, including autonomous driving, and intelligent cockpit applications. • Investigate methods for deploying lightweight Small Language Models on edge devices for use cases such as car cabin controls and automotive conversational assistants. • Evaluate the performance, efficiency, and deployment feasibility of developed AI models through testing, benchmarking, and comparison with existing approaches. • Document project findings, implementation details, evaluation res
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