> Markdown version of [/jobs/ext/4638406-senior-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/4638406-senior-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Machine Learning Engineer

- **Company:** Peloton Interactive, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Android NDK, Artificial Neural Networks, Computer Vision, C++ (Programming Language), Profiling, Continuous Integration, Python (Programming Language), Machine Learning, Object Detection, Tensorflow, Model Compression, Software Engineering, Edge Inference, Pytorch, Deep Learning, Keras, Git, Discretization, Few-Shot Learning, Production Code, Objective C++, Recurrent Neural Networks
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25303_907f6a5790e69760f938b492a0b00ec3

## About the Role

* 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., * 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

## Description

This role is hybrid in New York City or the Bay Area!, * 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