Senior Machine Learning Engineer
Listed on 2025-12-02
-
IT/Tech
Machine Learning/ ML Engineer, AI Engineer
Join to apply for the Senior Machine Learning Engineer role at Peloton Interactive
ABOUT THE ROLE:
This role is hybrid in New York City or the Bay Area!
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.
- Must have proficiency in C/C++ and Python
- Proficiency in ML frameworks like PyTorch, Tensorflow, Keras, etc.
- Ability to quickly translate research work into high-quality production code with a strong sense of good system design.
- Deep understanding of various neural network architectures specifically applied to solve CV problems, such as CNN/LSTM/3DConvs/GNN/TCN/Metric Learning and transformer based architectures.
- 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:
- Hands on experience on Model Compression techniques such as Quantization, Pruning, Distillation
- Experience with one of the following frameworks:
Qualcomm SNPE, Tensorflow Lite, CoreML or other similar Edge Inference/NN Acceleration frameworks. - Experience developing software for consumer products on Mobile SoCs, within the Android NDK framework and/or using CoreML for iOS.
- Experience developing Deep Learning models, especially for Detection, Tracking, Sequential modeling, Transformers and Few-Shot Learning tasks.
- Experience with compute offloads to GPU, DSPs, etc.
- Experience with profiling and tracing tools.
- Experience with Objective-c, Swift
Compensation and Benefits
The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives and if the location for the job changes. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits.
We offer robust and comprehensive benefits including:
Medical, dental and vision insurance;
Generous paid time off;
Short-term and long-term disability; 401k; tuition reimbursement;
Employee Stock Purchase Plan;
Fertility and adoption support; paid parental leave; family care discounts; and more.
Base Salary Range: $200,750 USD - $246,600 USD
ABOUT PELOTON:
Peloton (NASDAQ: PTON) provides Members with expert instruction and world class content to create impactful and entertaining workout experiences. Founded in 2012 and headquartered in New York City, Peloton serves members across the US and internationally. For more information, visit
Peloton is an equal opportunity employer and complies with all applicable fair employment practices laws. If you would like to request any accommodations during the application process, please email: applicant
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).