Research Scientist

As a Research Scientist at Applied Intuition, your primary responsibilities include conducting pioneering research in autonomous systems, focusing on areas such as end-to-end autonomy and closed-loop simulation. Collaborating closely with other scientists and engineering teams, you will develop algorithms and models that are critical to enhancing our autonomy products. Additionally, publishing your research findings to top-tier conferences is an essential aspect of this role.

To qualify for the Research Scientist position at Applied Intuition, you should possess an MSc or PhD in machine learning, computer vision, or a related field with a strong focus on autonomy and robotics. A robust research record, particularly with publications in reputable conferences or journals in the fields of AI, computer vision, and robotics, is also highly valued.

For success as a Research Scientist at Applied Intuition, strong research skills and the ability to work both independently and collaboratively are crucial. Experience in areas such as reinforcement learning, traffic simulation, and multi-view perception will also be advantageous, as these skills align with the innovative projects you’ll be tackling in our cutting-edge research environment.

Collaboration is key at Applied Intuition. As a Research Scientist, you will work closely with other research scientists, interns, and engineering teams. This team-oriented approach allows for the sharing of ideas, testing of new algorithms, and advancing best practices in the autonomy industry, ensuring that your contributions have a significant impact on our product development.

The work environment at Applied Intuition is fast-paced and customer-focused, fostering innovation and creativity. As an in-office company located in Mountain View, California, you can expect a collaborative atmosphere where discussions, brainstorming, and joint problem-solving are encouraged, ultimately leading to valuable advancements in the field of autonomous systems.

In response to this question, you should outline your background in developing autonomous solutions, detailing specific projects where you successfully contributed to or led initiatives. Highlight any relevant research you have conducted, including publications, as well as the tools and technologies you utilized.

This question allows you to showcase your expertise by discussing various research methodologies you have employed. Explain experiences with techniques like supervised learning, reinforcement learning, and any experience with data gathering, processing, and evaluation that you've carried out in past roles or research projects.

When asked about your problem-solving approach, articulate the steps you take to analyze a challenge. Discuss your methods for formulating hypotheses, conducting experiments, analyzing data, and iterating based on findings, emphasizing collaboration with peers for feedback and insights.

In your answer, mention any resources you utilize to stay informed on the latest AI research and trends, such as subscribing to journals, attending conferences, or participating in webinars. Discuss how you apply new knowledge to your work and share insights with your team.

Respond by describing a specific instance where you faced a setback in your research. Highlight how you analyzed the failure, what you learned from it, and how this experience ultimately improved your future work as a researcher, showcasing your resilience and adaptability.

Focus on your process for ensuring reliability, including data validation techniques, running control studies, and peer reviews. Explain how you strive for reproducibility in your experiments and the importance of maintaining rigorous standards in research.

Elaborate on the value of collaboration by discussing past experiences where working with diverse teams led to successful outcomes, innovative ideas, or accelerated research results. Emphasize your openness to feedback and exchanging knowledge.

Mention specific tools, frameworks, and programming languages you frequently use, such as Python, TensorFlow, or MATLAB. Discuss projects where you applied these tools effectively and any relevant certifications or training you have completed.

Discuss your approach to prioritizing tasks, emphasizing the importance of setting clear goals and timelines. Share methods like using project management tools or frameworks that help you stay organized and ensure that deadlines are met without compromising research quality.

In your answer, express your enthusiasm for Applied Intuition's mission and values, particularly in the realm of advancing autonomous systems. Share how your career goals align with the company’s objectives and how you believe your skills can significantly contribute to the team and its success.