Perception Engineer

As a Perception Engineer at Tavus, you will be responsible for developing and deploying perception models that allow AI avatars to recognize emotions, estimate poses, and interpret scenes. You will also have ownership over the data pipelines needed for training and evaluating these models, collaborate with a team of researchers and engineers to integrate new systems into our products, and run experiments to improve accuracy and performance.

Candidates for the Perception Engineer role at Tavus should have 2-3+ years of experience in building computer vision or ML systems. Strong skills in Python and PyTorch, as well as a deep understanding of areas like facial recognition or generative vision models, are critical. A self-starter mindset with a passion for solving complex problems will also be beneficial.

At Tavus, Perception Engineers work on groundbreaking projects that involve creating foundational models for AI-generated video experiences. This includes working on tasks like emotion recognition, pose estimation, and implementing real-time models that enhance human-AI interaction. The environment encourages innovation and experimentation, making it an exciting role for technical minds.

A Perception Engineer at Tavus should be well-versed in Python and PyTorch, especially in the context of real-time video applications. Knowledge of facial recognition, emotion recognition, and 3D reconstruction will greatly benefit candidates. Experience with multi-modal learning, and research papers in computer vision is a plus.

Tavus provides a range of great benefits for the Perception Engineer role, including a flexible work schedule, unlimited PTO, and competitive healthcare. The company fosters a supportive work culture that emphasizes personal growth and impact, ensuring that employees enjoy their journey while contributing to the team's success.

When answering this question, focus on specific projects where you've successfully implemented computer vision models. Highlight your familiarity with technologies like Python and PyTorch and how you've applied them in real-time applications. Discuss any challenges you faced and how you overcame them to demonstrate your problem-solving abilities.

Detail the perception models you’ve worked on, such as emotion recognition or pose estimation. Explain the methodologies used, the data sets involved, and the outcomes achieved. Share your personal contributions to these projects and any specific technologies or techniques applied during development.

To effectively answer this question, share specific resources you engage with, such as journals, online courses, or conferences. Emphasize your commitment to learning through continuous education and how you’ve applied newly learned concepts to your work. Demonstrating your interest in ongoing research is crucial.

When responding to this question, outline the specific challenge, the steps you took to analyze it, and the strategies you implemented to find a solution. Highlight your analytical skills, creativity, and resilience, showing how you learned from the experience and made improvements for future projects.

Discuss optimization techniques you have utilized, such as model pruning, quantization, or transfer learning. Explain how you implement metrics to benchmark performance improvements and ensure robustness across diverse operational conditions while managing trade-offs between accuracy and speed.

Provide details about the data pipelines you’ve managed, including collection, annotation, and processing. Emphasize your understanding of how these processes are critical for model training and performance evaluation. Offer examples of challenges faced and how you ensured data quality and pipeline efficiency.

Demonstrate your ability to translate academic research into practical applications. Share experiences where you've incorporated innovative techniques from research papers into your work, highlighting your capability to bridge the gap between theory and practice while delivering real-world solutions.

Highlight your collaboration skills, emphasizing successful partnerships with researchers and engineers. Discuss how teamwork fosters innovation and drives projects forward. Provide examples where effective communication and collaboration led to successful outcomes.

Express your enthusiasm for working at the intersection of AI and human interaction as a key focus. Discuss the potential impact of perception models on enhancing user experience and your desire to contribute to groundbreaking projects that shape the future of human-AI interaction.

Convey your interest in Tavus's mission of creating natural human-AI interactions. Align your values with the company’s vision, demonstrating how your skills and passions resonate with the role of Perception Engineer. Mention specific aspects of Tavus's work culture or projects that excite you.