Software Engineer III, AI Edge Applied ML Experiences - #2685118
Date: vor 1 Stunde
Stadt: München
Vertragstyp: Ganztags
Arbeitsplan: Volle Tag
In most instances, this position requires in-person interviews as part of the hiring process.Minimum qualifications:
Germany: €106000 - €108000 (EUR) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages such as C++, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
- Experience with on-device ML SDKs/tooling, e.g., MediaPipe, TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN.
- Master's degree or PhD in Computer Science or related technical fields.
- Passion for innovation and a strong desire to push the boundaries of what's possible with on-device ML.
- Excellent communication and collaboration skills.
- Proven track record of leading and delivering successful AI/ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
Germany: €106000 - €108000 (EUR) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Produce multi-task generative models directly on-device to power real-time, low-latency image editing features.
- Develop clean, reusable, cross-platform C++ APIs and native wrappers (Android and iOS) to enable frictionless integration of ML experiences into major partner apps like Google Photos, Snapseed, and YouTube.
- Integrate and deploy multimodal on-device models (such as Gemma) to enable private, local intelligence across text, audio, image, and video natively on-device.
- Optimize and port advanced goal-segmentation models onto edge devices, transitioning server-side prototypes into highly efficient mobile GPU/TPU pipelines targeting real-time tracking.
- Design and build low-latency, on-device audio and speech pipelines (such as direct translation) by developing highly optimized C++ code and MediaPipe graphs.
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