Sr Software Engineer, AI Engineer

About the role

As an AI Engineer on the Camera 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.

Responsibilities

• 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.

Requirements

• Bachelor’s, Master’s, or PhD in Data Science, Mathematics, Computer Science, Computer Engineering, Electrical Engineering or related field and 3–5 years of relevant experience.
• Strong analytical and problem-solving skills.
• AI/ML experience in:
  • Computer vision
  • Data structures, curation, annotation, and pipelines
  • Model training, fine-tuning, and evaluation
• Programming and technical proficiency in Rust, C++, Python, Shell, Embedded Linux, and Git.

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, storytelling, and data wrangling/big data.
• MLOps/DevOps: DVC, CML, GTO, GitLab Pipelines.
• Cloud platforms: 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, and signal processing.
• Communication protocols: gRPC, MQTT, WebRTC, Wi-Fi, Bluetooth.
• Experience working with secure, scalable, high-availability, low-latency, and distributed solutions.
• Proficiency with JIRA and Confluence.