Research Engineer

To become a Research Engineer at Pallon, candidates typically need either a PhD focusing on Machine Learning or Computer Vision, having published work in renowned conferences, or at least 5 years of hands-on industry experience in taking Machine Learning projects from concept to production, complemented by a degree in Computer Science, Mathematics, or a related field.

As a Research Engineer at Pallon, your main responsibilities will include researching and developing computer vision methods for tasks like 3D reconstruction and object detection, converting your research into robust, production-ready code, collaborating with the team to improve research methodologies and software design, and mentoring fellow engineers.

At Pallon, Research Engineers utilize a diverse tech stack. This includes Deep Learning frameworks such as Python and Pytorch, for Computer Vision applications they may work with C++, OpenCV, Ceres, and Eigen, and for infrastructure management, tools like Slurm, Kubernetes, and Docker are key.

Pallon supports work-life balance for Research Engineers through flexible work arrangements, enabling team members to work from home or access our inspiring office space in Zürich. This adaptability allows for productivity while also promoting personal well-being.

The work culture at Pallon is characterized by collaboration, innovation, and a shared commitment to societal impact. As a Research Engineer, you'll be part of a supportive and fun environment where knowledge sharing and mutual learning are highly encouraged.

When addressing your experience with machine learning projects, focus on specific instances where you played a critical role in taking a project from the research phase to a production environment. Discuss challenges faced, your approach to problem-solving, and any measurable outcomes that highlight your contributions.

In your response, outline key computer vision techniques like 3D reconstruction, object detection, and segmentation. Provide examples of how you've effectively implemented them in previous roles and how they can be applied to Pallon's sewer inspection applications.

When discussing your debugging approach, emphasize systematic troubleshooting methodologies, such as isolating components and conducting thorough tests. Mention specific tools or languages you’ve used and share an example of a tricky debugging scenario you navigated successfully.

Share your strategies for keeping up with industry trends, such as following leading publications, attending workshops or conferences, and participating in online communities. Illustrate the importance of continuous learning in your professional journey and how it relates to your role as a Research Engineer.

When answering this question, highlight instances where you’ve successfully collaborated with team members. Discuss your role in team dynamics, tools used for collaboration, and how effective communication contributed to project success. Show your understanding of the importance of teamwork in engineering.

To demonstrate your expertise, outline steps you take to optimize machine learning models, such as hyperparameter tuning, feature selection, and using diverse training strategies. Provide concrete examples that illustrate your process and the results achieved.

Discuss potential challenges like data quality, real-world variability, and computational demands. Showcase your problem-solving skills by suggesting practical strategies or solutions you've previously employed to overcome similar issues in your work.

Talk about your methods for task prioritization, such as using project management tools or setting clear goals. Mention how you balance urgent tasks with long-term projects and ensure that deadlines are met without sacrificing quality.

Convey the importance of mentorship in engineering for knowledge transfer and team growth. Share your own mentorship experiences, including how you’ve helped junior engineers rise in their careers and the positive impact it had on the team dynamics.

Be candid about your familiarity with Pallon’s tech stack, such as Python, Pytorch, and C++. Highlight any prior experience, how you've utilized these technologies in past projects, and a willingness to learn any unfamiliar aspects quickly.