1

Machine Learning Engineer Quantization Jobs in Phoenix, AZ

AI Solutions Architect

Tempe, AZ · On-site

$61.25 - $80.75/hr

... machine learning, and generative artificial intelligence use cases, including secure and high-availability deployment models • Collaborating with architects, engineers, data scientists, and ...

What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US: Seattle ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

AI Solutions Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US: Seattle ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Core AI / Machine Learning * Deep expertise in : Machine learning fundamentals (supervised ... Edge AI or model compression/quantization * AI safety research and explainability techniques

Core AI / Machine Learning * Deep expertise in : Machine learning fundamentals (supervised ... Edge AI or model compression/quantization * AI safety research and explainability techniques

Sr. Advanced AI Software Engineer

Phoenix, AZ · On-site

$115K - $152K/yr

Core AI / Machine Learning * Deep expertise in : Machine learning fundamentals (supervised ... Edge AI or model compression/quantization * AI safety research and explainability techniques

The AI Engineer is responsible for designing, building, and operationalizing intelligent systems ... Establish and enforce AI and machine learning and data operational standards, governance, and best ...

Work You'll Do As an AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Experience implementing and supporting endtoend Machine Learning workflows and patterns * Expert level programming skills in Python and experience with Data Science and ML packages and frameworks

AI/ML Engineer II

Phoenix, AZ · On-site +1

$113K - $136K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

AI/ML Engineer II

Phoenix, AZ · On-site

$116K - $139K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

See Phoenix, AZ salary details

$31.3K

$127.9K

$192.1K

How much do machine learning engineer quantization jobs pay per year?

As of Jun 28, 2026, the average yearly pay for machine learning engineer quantization in Phoenix, AZ is $127,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Phoenix, AZ? For Machine Learning Engineer Quantization jobs in Phoenix, AZ, the most frequently searched job titles are:
Sr. Engineer, Machine Learning Operations

Sr. Engineer, Machine Learning Operations

Exact Sciences

Phoenix, AZ • On-site

$209K/yr

Full-time, Part-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Exact Sciences rating

8.5

Company rating: 8.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

19th of 103 rated laboratories


Job description

Help us change lives

At Exact Sciences, we’re helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you’re working to help others.

Position Overview

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with cross‑functional partners—including biostatisticians, bioinformatics scientists, AI scientists, and software engineers—to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications. The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle—from data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying in‑depth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable, and aligned with the company's mission to help eradicate cancer.

Essential Duties

Include, but are not limited to, the following:

  • Designs, implements, and maintains end‑to‑end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real‑time inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production‑grade services integrated into customer‑facing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the company’s Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

  • Bachelor’s Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikit‑learn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time. 

Preferred Qualifications

  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.
#LI-CB1

Salary Range:

National Ranges: $ 123,000.00 - $209,000.00

California Ranges: $152,000.00- $228,000.00

 

The annual base salary shown is a national range for this position on a full-time basis and may differ by hiring location. In addition, this position is bonus eligible.

 

Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.

Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.

Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.

To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.


What Exact Sciences employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom