Machine Learning Engineer

Join an applied research team advancing the state of the art in Video AI for real-world perception systems. We operate at the intersection of computer vision research and large-scale product development, focusing on methods that enable robust 2D and 3D understanding of visual data. Our team owns the applied research lifecycle end to end—from problem formulation and data strategy, through model development, experimentation, and evaluation, working closely with production engineering teams to transition validated models into real products. We emphasize research rigor, empirical validation, and practical impact, translating novel ideas into deployable machine learning solutions under real-world constraints.

• Research and develop advanced methods for video perception, with a strong emphasis on both 2D and 3D understanding.
• Investigate approaches for tasks such as detection, tracking, scene understanding, reconstruction, and multimodal perception.
• Define data collection, curation, and annotation strategies to support effective training and evaluation of Video AI models.
• Train, evaluate, and refine models through systematic experimentation and quantitative analysis.
• Develop prototypes, reference implementations, and tooling to validate research ideas and guide downstream implementation.
• Partner closely with production engineering teams to transition research models into deployed systems, advising on architecture, performance trade-offs, and integration considerations.
• Stay current with advances in computer vision and applied machine learning research, and assess their applicability to real-world problems.

• Bachelor's, Master's, or PhD degree in Artificial Intelligence or a closely related field (e.g., Computer Vision, Machine Learning, Robotics, Computer Science).
• + Bachelor's degree plus 3 years of relevant experience in AI model research and training.
• + Master's degree plus 1 year of relevant experience in AI model research and training.
• + PhD degree with no additional industry experience required.
• OR
• Bachelor's, Master's, or PhD degree in a field not directly related to Artificial Intelligence: Minimum of 5 years of hands‑on experience in AI model research and training.
• Preferred Qualifications
• PhD or equivalent research experience in computer vision, 3D perception, robotics, or a closely related field.
• Experience with 3D perception techniques such as depth estimation, multi‑view geometry, point clouds, SLAM, or neural rendering.
• Strong hands‑on experience with deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with video pipelines, multimodal learning, or sensor fusion.
• Understanding of model deployment considerations such as latency, memory, robustness, and scalability, even if not directly responsible for production implementation.
• Experience collaborating across research, software, and product teams to deliver ML‑driven capabilities.
• Publications, patents, or open‑source contributions demonstrating applied research impact.

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