Machine Learning Engineer

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 Tensor

  Flow, Keras, and Py

  Torch. 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.