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AI Enabled Autonomous Systems Intern

Visteon · Detroit, US

Job description

Job Description

Visteon is advancing mobility through innovative technology solutions that enable a software-defined future. Our state-of-the-art product portfolio merges digital cockpit innovations, advanced displays, AI-enhanced software solutions, and integrated EV architecture solutions. With expertise spanning passenger vehicles, commercial transportation, and two-wheelers, Visteon partners with global automakers to create safer, cleaner, and more connected journeys. Headquartered in Van Buren Township, Michigan, Visteon operates in 17 countries, employing a global network of innovation centers and manufacturing facilities. In 2024, we recorded annual sales of approximately $3.87 billion and secured $6.1 billion in new business. What You’ll Do in This Role: Visteon is seeking an intern to join the Cockpit Product Line supporting development of AI enabled autonomous and ADAS related cockpit intelligence. In this role, you will:* Support the design, development, and rapid prototyping of AI/ML models that enhance autonomous‑ready cockpit functions, including perception‑driven cues, driver readiness and handoff assessment, driver state understanding, and situational awareness modeling.

  • Collaborate with system and platform architects to integrate lightweight Edge‑AI models into next‑generation cockpit compute platforms, enabling real‑time interaction layers for autonomous and semi‑autonomous driving experiences.
  • Execute end‑to‑end model development pipelines, including dataset preparation, training, hyperparameter tuning, validation, and performance optimization using state‑of‑the‑art AI frameworks.
  • Analyze multimodal automotive datasets (camera streams, radar metadata, CAN/Ethernet vehicle signals, driver monitoring outputs, and vehicle state information) to generate labels, evaluate model quality, and extract actionable insights that support autonomous behavior reasoning.
  • Benchmark and validate AI model performance against real‑time automotive constraints—latency, determinism, compute efficiency, thermal limits, memory footprint, and in‑vehicle reliability requirements.
  • Support development of proof‑of‑concept features showcasing intelligent cockpit‑autonomy collaboration, including driver takeover readiness assessment, adaptive HMI based on environmental conditions, predictive alerts, and proactive safety experiences.
  • Prepare well‑structured technical documentation, including experiment results, model evaluation summaries, architecture notes, and demo reports for internal engineering teams and customer‑facing reviews.

What’s In It for You:* Experience with AI models that interface with Autonomous systems.

  • Exposure to real-time embedded inference and safety-critical design considerations.
  • Opportunity to work with global teams at the intersection of cockpit, ADAS, and autonomy.
  • Hands-on experience with multimodal data and scenario modeling used in autonomous interaction.
  • Experience contributing to innovative prototypes shaping the future of autonomous-ready cockpits.

What You’ll Bring:* Education: Pursuing a Bachelor’s or Master’s in Computer Engineering, Electrical Engineering, Robotics, AI/ML, or related field.

  • Knowledge: Coursework or project experience in perception, sensor fusion, ADAS/AV systems, or machine learning.
  • Tools: Familiarity with Python, PyTorch/TensorFlow, ROS, OpenCV, AI compilers/deployment tools (TensorRT/ONNX).
  • Skills: Strong analytical thinking, experimental rigor, and comfort working with real-time data and embedded platforms.
  • Communication: Strong documentation, communication, and cross-functional teamwork skills.

Where You Will Work: This position will be based at Visteon’s Headquarters in Van Buren Township Michigan, GLCC, 40 hours per week for 12 weeks (14-22 weeks. 22 weeks preferred). Job Snapshot Updated Date 08-Apr-2026 Job ID J10726 Job Discipline Internship Location Grace Lake Corp Center, Van Buren Twp, Michigan, United States Employee Type Non FTE Employee Subtype Student

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