Senior Research Engineer

Senior Research Engineers at Hedra are responsible for designing and implementing machine learning models, especially focusing on 3DVAE and video diffusion models. They ensure that these models not only meet performance benchmarks but also handle data preparation efficiently for training. This involves conducting experiments and collaborating with the research team to apply theoretical findings in practical contexts.

To qualify for the Senior Research Engineer role at Hedra, candidates should hold a Master’s degree or PhD in Computer Science, Machine Learning, or a related field with a focus on data-driven ML. Additional qualifications include extensive experience in developing machine learning models, programming skills in Python, and knowledge of generative models, particularly VAEs and diffusion models.

At Hedra, Senior Research Engineers must possess strong programming skills in Python. Familiarity with deep learning frameworks is also crucial, as these tools are often used for implementing and optimizing machine learning models related to video generation and other generative media.

The work environment at Hedra is dynamic and collaborative, centered in San Francisco. As a Senior Research Engineer, you’ll be part of a passionate team eager to innovate and change the content creation landscape. There is a strong emphasis on teamwork and mentoring, fostering a supportive atmosphere where ideas can flourish.

Senior Research Engineers at Hedra enjoy a comprehensive benefits package, including competitive compensation, equity options, a 401(k) plan, healthcare covering medical, vision, and dental, as well as complimentary lunches and snacks at the office. These benefits reflect our commitment to supporting our team both personally and professionally.

When designing a machine learning model for video generation, I would start by defining clear objectives and performance benchmarks. This would involve selecting the right architecture, such as 3DVAE or diffusion models, and preprocessing the data efficiently. I would also emphasize iterative experimentation, closely monitoring performance metrics, and making adjustments based on findings.

Generative models play a crucial role in machine learning by enabling the creation of new data samples that are similar to the training data. In applications like video generation, they facilitate creative, novel content generation, enhancing visual storytelling and interaction through multimedia.

I focus on automating and streamlining data handling processes, ensuring that large video and 3D datasets are organized and cleaned before training. Effective strategies include normalization, data augmentation, and possibly utilizing specialized libraries to handle specific data types, which optimizes the training process.

I measure the performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score, depending on the specific application. For video generation, qualitative assessments are also important, where I evaluate the outputs subjectively and compare them with established industry benchmarks.

Key leadership qualities for a Senior Research Engineer include effective communication, empathy, and the ability to inspire and mentor team members. Being adaptable in dynamic environments and fostering a collaborative spirit within the team are also crucial for encouraging innovation and shared success.

I once worked on a project involving the development of a generative model for creating realistic video outputs. The biggest challenge was optimizing the model to handle large datasets efficiently. I approached this by breaking down the project into manageable tasks, running parallel processes, and continuously conducting performance evaluations to refine the model.

I find the potential of video diffusion models to create high-quality, dynamic visual content incredibly exciting. They introduce new ways to explore creativity and storytelling, and being part of that innovation at Hedra fuels my passion for pushing the boundaries of what's possible in generative media.

I believe the future of AI-driven content creation will see enhanced personalization and interactivity, where AI not only generates content but also learns from user preferences and feedback. This evolution will create richer experiences, transforming how we consume and interact with media.

Collaboration is integral to my role as a Senior Research Engineer. Working closely with teams brings diverse perspectives into the development process, enhancing creativity and innovation. Sharing knowledge and insights fosters a better understanding of complex problems, driving success in our projects.

I stay updated with the latest advancements in machine learning and AI by regularly reading academic journals, attending conferences, and participating in online forums and workshops. Engaging with the community and collaborating on open-source projects also provides valuable insights into emerging technologies and trends.