Sr. Machine Learning Engineer, Deployment (Edge)
Apply NowCompany: Peloton Interactive, Inc.
Location: New York, NY 10025
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 with one or more of:
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: applicantaccommodations@onepeloton.com.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions.
Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address.
If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence.
Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.
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 with one or more of:
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: applicantaccommodations@onepeloton.com.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions.
Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address.
If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence.
Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.