Sr. Machine Learning Engineer, Deployment (Edge) - Peloton Interactive : Job Details

Sr. Machine Learning Engineer, Deployment (Edge)

Peloton Interactive

Job Location : New York,NY, USA

Posted on : 2025-04-29T00:50:09Z

Job Description :

ABOUT THE ROLE:The AI/CV team is working on powering products that incorporate computer vision into the fitness domain. We are looking for a Senior Machine Learning Engineer, Deployment focused on Deep Learning/Computer Vision. The role will involve working closely with ML and Systems Engineers to ensure the success of ML applications on device, defining processes for packaging and deploying ML projects, and guiding the team on best practices for managing multi-dependency modules.

Responsibilities:

  • Collaborate and work closely with engineers to translate and deploy new AI/ML solutions for connected fitness devices.
  • Be the voice in the room that guides development work by ensuring work being done by the team is deployable in an end-to-end system.
  • Ensure model performance remains within expected bounds when promoting experimental models to production.
  • Specifically, you may encounter projects focused on: Temporal modeling, Object Detection, Segmentation, Perception, Multi-modal and Ensembling.

    • Qualifications:

  • Hands-on, real-world experience with one or more of Computer Vision, Machine Learning, Deep Learning.
  • Hands-on experience on Model Compression techniques such as Quantization, Pruning, Distillation.
  • Proficiency in C/C++ and Python.
  • Proficiency in ML frameworks like PyTorch, Tensorflow, Keras, etc.
  • Experience with one of the following frameworks: Qualcomm SNPE, Tensorflow Lite, CoreML or other similar Edge Inference/NN Acceleration frameworks.
  • Ability to quickly translate research work into high-quality production code with a strong sense of good system design.
  • Comfortable working with large image and video datasets.
  • Experience working in a CI/CD environment and git.
  • Excellent written and verbal communications skills.

    • Bonus Points:

  • Experience developing Deep Learning models, especially for Detection, Tracking, Sequential modeling, Transformers and Few-Shot Learning tasks.
  • Experience developing software for consumer products on Mobile SoCs, within the Android NDK framework and/or using CoreML for iOS.
  • Experience with compute offloads to GPU, DSPs, etc.
  • Experience with profiling and tracing tools.
  • Experience with Objective-C, Swift.

    • ABOUT PELOTON:

    Peloton (NASDAQ: PTON) provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together innovative hardware, distinctive software, and exclusive content. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com.

    Peloton is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. Equal employment opportunity has been, and will continue to be, a fundamental principle at Peloton, where all team members, applicants, and other covered persons are considered on the basis of their personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or any other protected characteristic as established by applicable law. This policy of equal employment opportunity applies to all practices and procedures relating to recruitment and hiring, compensation, benefits, termination, and all other terms and conditions of employment. If you would like to request any accommodations from application through to interview, please email: [email protected].

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