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Research Engineer

1 month ago

Redmond, United States Insight Global Full time

An AR/VR research company in Redmond, WA has a goal to explore, concept, and design novel interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of an always-on AR device that can provide contextually relevant assistance across a range of complex, dynamic, real-world tasks in natural environments.

To this end, we are looking for a research engineer who can accelerate the team’s research engineering efforts.

Day to day:

  • Build and maintain data and machine learning pipelines, including the consumption and integration of data from a variety of sensors.
  • Design, build and test machine learning systems for real-time sensing and inference (e.g., real-time pose estimation, hand-object recognition, task recognition).
  • Collaborate with other researchers and engineers to advance research in machine learning methods and applications.

Must haves:

  • Bachelors in computer science, computer vision, machine learning, artificial intelligence, human-computer interaction, robotics, or related technical field.
  • 3+ years of experience with Python
  • Experience with at least one deep-learning software library (e.g., PyTorch, Caffe2, TensorFlow), including formulation, training, and evaluation of new algorithms and writing reusable modules.
  • 3+ years of experience utilizing general software engineering skills, including debugging, version control, logging, documentation, code review, etc.
  • 3+ years of experience building ML solutions (ideally from scratch as well as improving on existing) for challenging real-world interactive applications and proving them through end-to-end prototypes and/or products.

Plusses:

  • Masters or PhD degree in related field
  • Experience with hand, eye, and/or body tracking.
  • Experience with multimodal modeling, embeddings, and/or time-series modeling.
  • Experience designing data-collection protocols and recording datasets for machine-learning systems.

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