Machine Learning Engineer

Role Overview

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.

Your Impact

As a Video AI Applied Research Engineer, you will :

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

Minimum Qualifications

Bachelor’s, Master’s, or PhD degree in Artificial Intelligence or a closely related field (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

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

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

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