Intern Jobs

About The Position

Requirements

• Currently enrolled in a Master’s or Ph.D. program in Computer Science, Electrical Engineering, or a related field with a focus on ML/AI.
• Strong foundational understanding of CNNs, RNNs (LSTMs), or Transformer-based architectures.
• Hands-on experience with Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX).
• Basic familiarity with processing time-series, audio, or sensor data.
• Eager to work in a high-ambiguity "startup" environment within a larger corporation.
• Ability to explain complex technical findings to a multi-disciplinary team of hardware and software engineers.

Nice To Haves

• Experience or coursework in C/C++ or working with resource-constrained hardware (e.g., Raspberry Pi, ESP32, ARM Cortex-M).
• Familiarity with TFLite, ONNX, or similar edge deployment toolchains.
• Previous research experience or publications in areas like anomaly detection, reinforcement learning, or generative AI for signal processing.
• Contributions to open-source ML projects or active participation in academic labs.

Responsibilities

• Assist in building and testing ML models for edge intelligence, specifically focusing on audio, sensor, and control signals.
• Support the design of model architectures and contribute to data labeling strategies, synthetic data generation, and augmentation pipelines.
• Explore and implement model compression techniques—such as quantization, pruning, and knowledge distillation—to ensure models run efficiently on embedded systems.
• Stay current on foundation/SLM trends and academic research; help define benchmarks and evaluation metrics to measure the success of CVL’s ML prototypes.
• Partner with firmware, silicon, and systems engineers to understand the physical constraints of hardware and how they impact algorithmic accuracy.