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Internship Machine Vision Engineer Jobs in Arizona

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$150K - $198K/yr

Our client is seeking a Sr. Machine Learning Engineering for a direct hire role to sit in North ... machine vision systems. * Develop scalable architectures capable of processing large volumes of ...

This role provides specialized technical expertise in PLC programming, robotics integration, machine vision systems, motion controls, industrial networking, and automated manufacturing equipment.

As an Automation Engineer , you will design, develop, and support automated manufacturing equipment ... This role will focus on integrating motion systems, sensors, robotics, machine vision, safety ...

This role provides specialized technical expertise in PLC programming, robotics integration, machine vision systems, motion controls, industrial networking, and automated manufacturing equipment.

This role provides specialized technical expertise in PLC programming, robotics integration, machine vision systems, motion controls, industrial networking, and automated manufacturing equipment.

General Application for Interns

Chandler, AZ · On-site

$14.75 - $19/hr

Hands-on assembly and machining experience a plus * Experience with software programming a plus ... machine vision and robot & laser integration. AeroSpec is ISO 9001 compliant; provides CE ...

Sr Hardware Engineer

Arizona City, AZ · On-site

$116.60 - $194.40/hr

We collaborate closely across Quality Engineering, Regulatory, R&D, Equipment Engineering, and ... Leveraging your expertise in PLCs, machine vision systems, automation, and data analytics, you will ...

Job's mission As a Senior Systems Engineer (Mechatronics and Robotics) at ASM, you'll design and ... Your expertise in control systems, machine vision, and servo integration will help us deliver ...

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Internship Machine Vision Engineer information

What types of projects do internship machine vision engineers typically work on, and how do they collaborate within the team?

As an Internship Machine Vision Engineer, you will often be involved in projects that focus on developing and testing computer vision algorithms, working with image processing tools, and supporting the integration of machine vision systems into larger automation solutions. You’ll collaborate closely with senior engineers, software developers, and sometimes hardware teams to validate solutions and troubleshoot issues. Regular meetings, code reviews, and shared project management tools help ensure smooth communication and learning opportunities, fostering both technical growth and teamwork.

What are the key skills and qualifications needed to thrive as an internship machine vision engineer, and why are they important?

To thrive as an Internship Machine Vision Engineer, you generally need a background in computer science, electrical engineering, or a related field, with foundational knowledge in image processing and computer vision algorithms. Familiarity with programming languages such as Python or C++, experience with tools like OpenCV, and exposure to machine learning frameworks are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork are the soft skills that set outstanding candidates apart. These competencies are crucial for efficiently developing, testing, and deploying vision solutions that address real-world automation and inspection challenges.

What does an internship machine vision engineer do?

An Internship Machine Vision Engineer assists in developing and implementing computer vision algorithms to enable machines or robots to interpret visual data. Their tasks often include image processing, object detection, camera calibration, and working with various sensors. Interns typically support senior engineers in testing, data collection, and model optimization, gaining hands-on experience with real-world applications. This role offers valuable exposure to fields like automation, robotics, and artificial intelligence, helping interns build a foundation for a career in machine vision.
What are the most commonly searched types of Machine Vision Engineer jobs in Arizona? The most popular types of Machine Vision Engineer jobs in Arizona are:
What cities in Arizona are hiring for Internship Machine Vision Engineer jobs? Cities in Arizona with the most Internship Machine Vision Engineer job openings:
Infographic showing various Internship Machine Vision Engineer job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Sr. Machine Learning Engineer

Prosum Inc.

Phoenix, AZ • On-site

$150K - $198K/yr

Other

Posted 4 days ago


Job description

Job Description
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.

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