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Urgently Hiring Machine Learning Engineer New Grad Jobs in Arizona

Prosum Inc.

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

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 ...

Intel

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

... apply, and our hiring team will be glad to contact you when/if relevant. Qualifications ... Ability to learn new technologies fast and adapt to changes with open-mindedness. Requirements ...

MY DR NOW

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

Knowledge of Machine Learning and Generative AI frameworks * Strong engineering fundamentals and problem-solving skills * A builder mindset -- curious, resourceful, fast-moving, and focused on ...

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Urgently Hiring Machine Learning Engineer New Grad information

What does a machine learning engineer new grad do?

An entry-level Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models to solve real-world problems. They work closely with data scientists, software engineers, and product teams to collect and preprocess data, select appropriate algorithms, and integrate models into production systems. New grads in this role often focus on learning industry best practices, improving model performance, and collaborating on cross-functional projects under the guidance of more senior engineers. They may also participate in code reviews, documentation, and continuous learning to stay updated with advancements in machine learning.

What are some common challenges new graduates face when starting as a machine learning engineer, and how can they overcome them?

New graduates entering Machine Learning Engineering often find it challenging to bridge the gap between academic knowledge and real-world applications, especially when dealing with large, messy datasets and ambiguous business objectives. Collaborating effectively with cross-functional teams—such as data engineers, product managers, and software developers—can also be a learning curve, as clear communication and understanding of broader project goals are essential. To overcome these challenges, new grads should seek mentorship, actively participate in code reviews, and focus on continuously improving their coding and problem-solving skills through hands-on projects. Embracing feedback and staying updated with industry best practices will also accelerate their professional growth.

What are the key skills and qualifications needed to thrive as a machine learning engineer new grad, and why are they important?

To thrive as a Machine Learning Engineer New Grad, you need a solid background in computer science, statistics, and programming (especially Python), typically supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems is commonly required. Strong problem-solving abilities, teamwork, and effective communication help new grads excel in collaborative and fast-evolving environments. These skills ensure the ability to build, deploy, and continually improve machine learning models that solve real-world problems.

What are the most commonly searched types of Machine Learning Engineer New Grad jobs in Arizona?

The most popular types of Machine Learning Engineer New Grad jobs in Arizona are:

What are popular job titles related to Urgently Hiring Machine Learning Engineer New Grad jobs in Arizona?

For Urgently Hiring Machine Learning Engineer New Grad jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Urgently Hiring Machine Learning Engineer New Grad jobs in Arizona look for?

The top searched job categories for Urgently Hiring Machine Learning Engineer New Grad jobs in Arizona are:

Urgently Hiring Machine Learning Engineer New Grad jobs near you
Infographic showing various Urgently Hiring Machine Learning Engineer New Grad job openings in Arizona as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Sr. Machine Learning Engineer

Prosum Inc.

Phoenix, AZ • On-site

$130K - $150K/yr

Other

Posted 18 days ago

Job description

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.

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