Machine Learning Engineer

Prosum; Phoenix (AZ); Hybrid; USD 130,000 - 150,000; Full time

Job summary

Prosum in Phoenix, AZ is seeking a Senior Machine Learning Engineer to architect and optimize real-time image pipelines for high-throughput CV applications. The role focuses on CUDA kernel tuning, GPU parallelism, and deploying ML models in production-grade C++/Python code.

The position offers hybrid work, with onsite presence in North Phoenix or Hillsboro, OR, and a salary range of $130k to $150k per year. Join a team advancing high-performance image processing at scale.

Qualifications

• Experience building high-throughput, real-time image pipelines.
• Strong proficiency in CUDA kernel tuning and GPU optimization.
• Experience deploying ML/CV models in production with C++/Python.

Responsibilities

• Design and optimize real-time imaging pipelines for inspection systems.
• Develop CUDA kernels and optimize GPU utilization.
• Deploy and validate ML models using production-grade code in C++/Python.
• Collaborate with hardware and software teams.

Skills

CUDA kernel programming

GPU acceleration

C++

Python

Real-time processing

High-throughput pipelines

Multi-threading

Model deployment

Profiling

TensorRT ONNX

Tools

TensorRT

ONNX Runtime

CUDA Toolkit

Profiling tools

NVIDIA GPUs

Job description

## Machine Learning Engineer**Phoenix,AZ85083**Employment Type:PermJob Number: 25827Remote Options: Hybrid## Job Description**Sr. Machine Learning Engineer** *Salary Range: $130k to $150k* Our client is seeking a Sr. Machine Learning Engineering for a direct hire role to sit in North Phoenix, AZ or Hillsboro, OR. This role will be onsite 4 days a week and 1 remote day. **JOB SUMMARY** The role of Senior Machine Learning Engineer will architect and optimize real-time, high-throughput, and ultra-low latency image pipelines for next-generation Mask Inspection Tools. Responsibilities include eliminating hardware bottlenecks through CUDA kernel tuning and GPU parallel computing, ensuring deep learning models and CV algorithms seamlessly processing massive, high-bandwidth streaming data at production scale. **ESSENTIAL DUTIES AND RESPONSIBILITIES** **High-Performance Computing Pipeline Architecture*** Design, implement, and optimize high-throughput, low-latency image processing pipelines for real-time optical inspection and machine vision systems.* Develop scalable architectures capable of processing large volumes of imaging data while meeting stringent latency and reliability requirements.* Profile and optimize system performance across CPU, GPU, memory, and I/O subsystems.**GPU Acceleration*** Design, develop, and optimize CUDA kernels to accelerate deep learning inference and classical computer vision algorithms.* Maximize GPU utilization through efficient memory management, kernel optimization, and parallel programming techniques.* Evaluate and implement performance improvements using NVIDIA GPU technologies and profiling tools.**Model Deployment & Optimization*** Optimize, quantize, and deploy machine learning models using TensorRT, ONNX Runtime, or similar inference frameworks.* Integrate AI models into production-grade C++ and Python applications.* Improve inference throughput, latency, and resource utilization while maintaining model accuracy.* Develop automated deployment and validation pipelines for machine learning models.**Concurrency & Systems Optimization*** Architect and implement multi-threaded, high-concurrency software components for data acquisition, buffering, streaming, and real-time processing.* Design robust synchronization and communication mechanisms between hardware interfaces and AI processing pipelines.* Optimize end-to-end system performance for deterministic, real-time execution.**Cross-Functional Collaboration*** Partner with machine learning scientists, computer vision engineers, hardware engineers, and software developers to deliver integrated AI solutions.