Machine Learning Engineer

As a contractor, you will collaborate with a highly energetic, global, and innovative team. You will participate in various development phases of next-generation machine learning systems.

Your responsibilities

- Framework Implementation: Implement and integrate ML programming framework on

embedded platforms and multi-core architectures.

- Integration: Integrate embedded applications and algorithm libraries both pre and post

silicon into NXP software stack.

- System Integration: Perform system-level integration and validation for heterogeneous

platforms including DSPs and accelerators.

- Algorithm Integration: Integrate state-of-the-art ML algorithms for automotive domain,

such as driver identification, predictive maintenance,

- Model Deployment: Deploy and integrate models on resource-constrained embedded

systems.

Who we’re looking for

To ensure your success in this role, the following experience is needed:

Must have skills:

- Processor Knowledge: Good knowledge of processor architecture and micro-architecture (e.g.,

SIMD/GPGPU/NEON).

- Software Integration: 3+ years of hands-on experience in software integration and development

on complex embedded computing platforms.

- Mathematical Background: Good understanding of how algorithms work, such as image

processing or neural networks.

- Programming Languages: Proficiency in C and C++.

Any of the following are pluses:

- Embedded ML Frameworks: Experience with frameworks like TensorFlow Lite, Glow, PyTorch Mobile, or ONNX Runtime. Understanding of model quantization and optimization techniques for embedded deployment.

- DSP Algorithms: Prior work on DSP algorithms, neural networks kernel libraries or audio processing.

- Standards Knowledge: Familiarity with Automotive SPICE, Functional Safety (ISO26262), and coding guidelines like MISRA or AUTOSAR.

- Performance Optimization: Expertise in performance optimization on embedded

platforms with ARM NEON or accelerator/DSP.

- Hardware Knowledge: Background in electronic hardware or close to hardware level.

Attentive to details, self-motivated and able to be a team player while working independently