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Senior, Computer Vision Researcher / Engineer, Localization

Job Description

As a Senior, Computer Vision Researcher / Engineer on the Large Scale Localization and Mapping team, you’ll be exposed to and tasked to deliver solutions with state-of-the-art computer vision capabilities. Your code will be part of the foundations of our 3D platform that enables the next generation of computing applications for many years to come. In this position, you will work on developing and optimizing perception algorithms on cloud and on embedded platforms.

Responsibilities:

• Research, dev elop and productize computer vision algorithms for state-of-the-art performance critical large-scale localization and mapping systems.
• Own and drive highly visible performance metrics (e.g. latency, memory, bandwidth, power).
• Collaboratively work as part of a fast paced team, analyze and optimize a growing C++ and Python codebase.
• Own and drive the integration of the team’s perception systems into the Magic Leap software ecosystem.
• Help define performance standards for algorithms, develop and drive best practices (performance, maintainability, correctness, etc), provide guidance at all stages of the software development cycle and share knowledge.
• Help drive the integration and development of necessary tooling and automation (profiling, testing/verification, monitoring, etc) that allows the team to move even faster.
• Participate in architecture design, development planning and prioritization for the team’s perception algorithms.

Qualifications:

• 3+ years of practical experience in C++, Python with high performance / low latency applications
• 3+ years of experience in geometric computer vision, SfM / SLAM, 3D reconstruction, visual odometry, sensor fusion, or similar
• Strong CS fundamentals, problem-solving skills, high quality coding, performance analysis and debugging skills
• Strong sense of curiosity, fast learner

Preferred / additional skills:

• Numerical computing, modeling, simulation
• Familiarity with machine learning techniques for geometric computer vision problems
• Experience in code optimization, memory optimization, understanding of abstraction and modularity, critical path optimization and tuning
• In depth understanding of computer architecture, computing bottlenecks, memory hierarchy, data coherency, caches, high performance architectures (VLIW, superscalar, etc), SIMD, concurrent systems, parallelization, compilers, system simulators
• Experience with SW development for embedded platforms
• Experience in developing and maintaining large software projects

Education:

• BA/BS in CS, EE or similar required. MS, Ph.D. preferred

Additional Information:

• All your information will be kept confidential according to Equal Employment Opportunities guidelines