Machine Learning Engineer

Immediate need for a talented Machine Learning Engineer. This is a 06+months contract opportunity with long-term potential and is located in Redmond ,WA(Hybrid). Please review the job description below and contact me ASAP if you are interested.
Job ID:26-32118
Pay Range: $75 - $82/hour.  Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:

• Collaborate with research scientists to transition ML models from research prototypes to efficient, real-time inference on embedded devices.
• Train, fine-tune, and adapt ML models while considering deployment constraints such as latency, memory, power, and compute requirements.
• Optimize models for on-device inference using techniques such as quantization, pruning, knowledge distillation, operator fusion, and architecture adjustments.
• Port, integrate, and profile ML models on embedded targets, including DSPs, NPUs, microcontrollers, and mobile system-on-chips (SoCs), identifying and resolving performance bottlenecks.
• Develop clean, maintainable, high-performance C/C code for on-device inference pipelines and integrate it into real-time prototype systems.
• Build tools and infrastructure that enable researchers to evaluate model performance and accuracy more efficiently on target hardware.
• Coordinate with internal hardware, runtime, and toolchain teams to evaluate and integrate models with existing systems.
• Collaborate effectively within a cross-functional team that values communication, documentation, and teamwork.
• Continuously learn new technologies, explore unfamiliar technical areas, and embrace the challenges and ambiguity of AR/VR development.

Key Requirements and Technology Experience:

• Experience with audio machine learning, including speech enhancement, source separation, keyword spotting, or acoustic event detection.
• Experience with computer vision machine learning, including object detection, tracking, segmentation, or pose estimation.
• Knowledge of audio DSP fundamentals, including filtering, short-time Fourier transforms (STFT), filter banks, beamforming, and real-time audio processing.
• Experience with on-device inference frameworks and toolchains such as ExecuTorch, TensorFlow Lite/LiteRT, ONNX Runtime, or vendor-specific NPU/DSP SDKs.
• Experience with model compression techniques, including quantization-aware training, post-training quantization, pruning, and knowledge distillation.
• Experience implementing hardware-specific optimizations, such as SIMD/NEON, DSP intrinsics, and fixed-point arithmetic.
• Experience working in the AR/VR or wearable device industry.
• Ability to gather requirements and collaborate closely with researchers to develop client solutions.
• Proven experience writing software to support the execution of research initiatives.
• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent work experience.
• 2+ years of industry experience optimizing and deploying ML inference on embedded or resource-constrained devices.
• Experience training ML models using deep learning frameworks such as PyTorch or TensorFlow.
• At least 2 years of industry experience writing C/C code.
• Experience profiling and debugging performance issues across ML models and target hardware.
• Experience working in cross-functional teams.

Our client is a leading Social Media Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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