Research Engineer

As a Research Engineer at Hedra, your primary responsibilities will include implementing and testing machine learning models, particularly focusing on 3DVAE and video diffusion models. You'll assist in data preparation for training models, stay updated with the latest trends in machine learning, and contribute to the development of new features that enhance our models. Collaboration with your team will be essential to achieving project goals.

To qualify for the Research Engineer role at Hedra, candidates should possess a Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field. Some experience with machine learning projects, particularly in Python and with frameworks like PyTorch or TensorFlow, is essential. Strong programming skills and a willingness to learn are critical for this early-career position.

While startup experience is beneficial for the Research Engineer position at Hedra, it is not a strict requirement. We value candidates who are self-starters, driven, and eager to tackle new challenges, regardless of their previous work environment. Diverse perspectives are welcomed, and your unique skills could be a great asset to our team.

At Hedra, new Research Engineers can expect a collaborative and supportive team environment. The emphasis is on continuous learning, sharing ideas, and contributing to exciting projects. You'll work alongside talented team members, fostering experiences that allow for innovation and professional growth.

Hedra offers a competitive compensation package that includes equity, a 401k plan, healthcare benefits (including medical, vision, and dental), as well as complimentary lunch and snacks in the office. We are committed to supporting our team and ensuring a healthy work-life balance.

When addressing this question, focus on specific projects where you utilized machine learning algorithms, tools, or frameworks, particularly with Python, PyTorch, or TensorFlow. Describe your role, challenges faced, and results achieved to showcase your capabilities.

Discuss your experience with data collection, cleaning, preprocessing, and splitting datasets for training and testing. Highlight any techniques or tools you've used to handle video datasets, as this is crucial for the position at Hedra.

In your response, provide a brief overview of diffusion models, explaining their significance in generating realistic data. If you have hands-on experience with these models, share how you implemented them and any insights gained during your work.

Mention the resources you utilize to keep abreast of developments in machine learning, such as research papers, blogs, online courses, and community forums. Emphasize your commitment to continual learning and applying new knowledge.

Use the STAR method (Situation, Task, Action, Result) to structure your answer. Discuss the challenge, your specific responsibilities, the steps you took to resolve it, and the positive outcome that resulted from your efforts.

Talk about your approach to time management, including tools or methodologies you employ, such as Agile or Kanban. Give examples of how you've effectively prioritized tasks to remain productive and meet project deadlines.

Emphasize the importance of collaboration, communication, and leveraging diverse strengths within a team. Provide examples of how you worked with others to achieve a project’s success and the value of sharing knowledge and skills.

Discuss elements such as data quality, feature selection, model architecture, evaluation metrics, and continuous monitoring. Share insights from any models you've worked with, explaining how these factors influenced their performance.

Illustrate how you view feedback as an opportunity for growth. Provide an example of how you've received constructive criticism, implemented changes, and the positive results that followed, fostering a mindset of continuous improvement.

Convey your enthusiasm for Hedra's mission and the exciting opportunity to work on innovative projects like Hedra Studio. Discuss your alignment with the company's values and culture, and how you see yourself contributing to their vision.