Job Description
About the Role :
As a software engineer on the AI team, you will work alongside a group of talented and collaborative engineers to create practical AI solutions that significantly enhance home protection, provide valuable insights, and increase daily convenience Our pioneering, fully integrated smart home ecosystem provides a unique platform to develop groundbreaking experiences in computer vision, sensor fusion, and advanced machine learning applications.
Your key responsibilities will encompass :
- Lead the design and development of high-quality, scalable AI features and products, focusing on customer benefits and technical excellence.
- Collaborate closely with cross-functional teams (embedded, apps, platform, QA, product, and UX) to successfully deploy AI solutions to our large customer base.
- Create, test, and refine advanced machine learning models, optimizing them for both edge and cloud environments.
- Develop comprehensive pipelines for data management, including curation, visualization, annotation, and model training processes.
- Continuously monitor and maintain the performance of AI features in production, ensuring ongoing customer value and discover iterative improvements.
Required Qualifications :
- Bachelor’s, Master’s, PhD in Data Science, Mathematics, Computer Science, Computer Engineering, Electrical
- Engineering or related field and 5-8 years of relevant experience
- Strong analytical and problem-solving skills
- AI / ML Experience :
- Data structures, curation, annotation, and pipelines
- Computer vision, model training, fine-tuning, and evaluation
- Programming and Technical Proficiency :
- Rust, C++, Python, Shell
- Embedded Linux
Preferred Qualifications :
- Computer Vision : Classification, Object Detection, Segmentation, Tracking, Recognition, VLM, Pose, Vector
- Embeddings, Re-ID, OpenCV
- ML frameworks : TensorFlow, PyTorch
- Data Engineering :
- FiftyOne, CVAT, Vertex AI, Label Studio
- Data Visualization / Story Telling and Data Wrangling / Munging / Big Data
- MLOps / DevOps : DVC, CML, GTO, Gitlab Pipelines
- Cloud : GCP (Vertex AI / Storage / Cloud Functions), AWS, Azure
- Databases : SQL, NoSQL, Vector, Time Series, Graph
- Transformers, LLMs, Knowledge Graphs
- Multimedia pipelines : GStreamer, ffmpeg, mediapipe
- Edge computing, Embedded Systems, and IoT Devices
- Model compression techniques
- Image, Audio, Radar, Signal Processing
- Communication Protocols : gRPC, MQTT, WebRTC, Wi-Fi, Bluetooth
- Experience working with secure, sc
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