AI Engineer - Connected & Autonomous Driving and Software-Defined Vehicles

As an AI Engineer at NIKI, your key responsibilities include developing innovative approaches to secure networked systems and ADAS/AD functionalities, coordinating interdisciplinary projects, and implementing AI-driven solutions for software-defined vehicles. You'll work closely with clients like Daimler and BMW, ensuring timely delivery of high-quality technical solutions while keeping up with industry advancements.

To qualify for the AI Engineer role at NIKI, you should possess knowledge in software engineering and develop AI-driven solutions. A strong interest in autonomous driving and good command of programming languages like Python, C++, or Java is essential. Familiarity with large language models and basic understanding of neural networks will also benefit your application.

An AI Engineer at NIKI should have excellent communication skills and a spirit of innovation. Self-motivation, strong problem-solving abilities, and analytical skills are vital for success in this role. Additionally, knowledge of standard libraries such as numpy and tensorflow, as well as experience in areas like Predictive Maintenance and Object Tracking, will give you an edge.

At NIKI, as an AI Engineer, you'll engage in diverse and innovative projects related to Artificial Intelligence, Connected & Autonomous Driving, and Automotive.OS. Your work will focus on developing groundbreaking tools and solutions while collaborating with cross-functional teams, ensuring you stay at the cutting edge of the automotive industry.

NIKI boasts a dynamic work culture that emphasizes collaboration, learning, and growth. You'll receive structured mentorship, professional feedback, and opportunities to take on responsibilities swiftly. Enjoy flexible working hours, excellent colleagues, and a culture that encourages knowledge sharing and innovation.

In answering this question, discuss specific projects or experiences that involved developing AI solutions for autonomous driving. Highlight your understanding of how AI improves vehicle functionalities, the technologies used, and any challenges faced during implementation.

Be prepared to talk about programming languages like Python, C++, or Java. Provide examples of past projects where these languages were used, emphasizing how you applied them to tackle specific challenges or achieve project objectives.

Share the methods you use to keep abreast of AI advancements, such as following industry news, attending webinars, or participating in relevant courses. Emphasize your proactive approach to learning and adapting to new technologies.

When responding, discuss specific neural network architectures you’re familiar with, like feed-forward neural networks or convolutional neural networks. Illustrate their applications in projects you've previously worked on and how this experience applies to the role at NIKI.

Use the STAR method (Situation, Task, Action, Result) to outline a specific situation where you encountered a problem. Describe the approach taken to resolve it, focusing on your problem-solving and analytical skills.

Discuss your strategies for fostering clear and open communication in team settings, emphasizing your experience collaborating with diverse teams. Mention practices like regular meetings, active listening, and using project management tools.

Be specific about the libraries you are familiar with, such as TensorFlow or scikit-learn. Explain how you have utilized these tools for data processing, machine learning, or developing AI-driven applications to solve real-world problems.

Provide a detailed response that demonstrates your understanding of the concept of software-defined vehicles. Discuss previous experiences related to their architectural design and how it influences system performance and capabilities.

Reflect on your passion for AI and its applications in the automotive industry. Share personal anecdotes or experiences that inspired you, and express how this motivation drives your work and ambitions.

Outline a strategic approach to such a project, including the initial research phase, collaboration with stakeholders, technology selection, project timeline, and how you would ensure the delivery of a high-quality solution.