Machine Learning Engineer
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Responsibilities
- Help collect and categorize data from public sources as well as from our customer base (when authorized).
- Support training data workflows — we outsource annotation, but data still needs validation and sometimes transformation for the target network.
- Improve test performance and ensure compatibility with new hardware — not only in the NVIDIA ecosystem with the Jetson edge platform, but also on programmable FPGAs and server-grade CPUs (e.g., Intel).
- Test, improve, and tune existing algorithms (neural networks, Bayesian/Markov models, decision trees, reinforcement learning networks, Gaussian models, etc.).
- Port existing solutions (and training data) to different frameworks.
Requirements
- We are technology-agnostic but favor TensorFlow, Keras, and PyTorch. Strong Python skills are important both for data analysis and for integrating with our Python-based backend.
- We require either practical work experience or solid theoretical knowledge (or both).
- Education: bachelor’s degree in a science or engineering discipline preferred; master’s degree or PhD is an advantage.
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