Senior Machine Learning Engineer

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

#LI-Hybrid

#LI-JS2