1

Machine Learning Engineer Quantization Jobs in Chicago, IL

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. As a Senior ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

Computer Vision Engineer As a Computer Vision Engineer, you will be part of our AI Team working on ... Hands-on experience applying machine learning and deep learning to vision data, preferably direct ...

Machine Learning Engineer

Niles, IL · On-site

$53 - $72.75/hr

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...

Machine Learning Engineer

Niles, IL · On-site

$53 - $72.75/hr

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...

Senior Machine Learning Engineer

Chicago, IL

$107K - $147K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

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

As of Jun 20, 2026, the average yearly pay for machine learning engineer quantization in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Chicago, IL look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Machine Learning Engineer Quantization jobs? Cities near Chicago, IL with the most Machine Learning Engineer Quantization job openings:
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Paylocity

Schaumburg, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 23 days ago

Be an early applicant


Paylocity rating

8.5

Company rating: 8.5 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

46th of 428 rated business services


Job description

Description:

Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.


While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.


We give our employees what they need to succeed, including great benefits and perks! We offer medical, dental, vision, life, disability, and a 401(k) match, as well as perks that support you, your family, and your finances. And if it’s career development you desire, we provide that, too! At Paylocity, people matter most and have always been at the heart of our business.


Help Paylocity enhance communication and enable employees to connect, collaborate, and create from anywhere with a position in Product & Technology!


Want to develop the strategies and principles needed to deliver compelling software? Join our team and help us enhance our all-in-one software platform, elevate our one-of-a-kind technology, and improve the employee experience.


Take your career to the next level at one of G2's Top 100 Software Companies. Explore our Product & Technology positions to see where you fit!


This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements.


Position Overview


Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users.


As a Staff Machine Learning Engineer in Product & Technology, you will help Paylocity build and deploy Machine Learning solutions, to help our teams build better products faster, more reliably, and at the scale we see in production for our customers. We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your primary focus will be to leverage your expertise in software development, machine learning algorithms, and data infrastructure to architect, develop, and optimize machine learning solutions. You will play a key role in driving the development of scalable and efficient machine learning models, contributing to the enhancement of product features, and the overall improvement of our infrastructure.


Our team is:

  • Building infrastructure that can power ML and AI features for millions of users
  • Building and deploying platform-wide recommendations to help companies follow HR best practices and allow employees to get the most out of our platform (Paylocity AI page)
  • Baking AI Ethics into all of our processes as a first-class citizen (Blog Post)
  • Working in a collaborative fully remote environment with a desire to share ideas and continuously improve
  • Invested in staying current in machine learning engineering by applying the newest tools, technologies, and practices
  • Excited to work on cutting-edge technology!


Primary Responsibilities

  • Collaborate closely with internal teams such as Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities.
  • Leverage cutting-edge big data technologies on AWS utilizing Databricks and Spark to develop scalable and efficient machine learning solutions for millions of users.
  • Create automated data and modeling pipelines, collaborating with internal teams to ensure smooth integration and deployment of machine learning software features.
  • Lead the optimization of CI/CD workflows, ensuring scalability and resilience while addressing complex challenges in automation in partnership with DevOps and Delivery Platforms.
  • Proactively identify and resolve issues/bugs, ensuring AppSec vulnerabilities are identified and corrected, working closely with Application Security and CCOE teams.
  • Drive the adoption of best practices in machine learning engineering across teams, contributing to the development of formal training programs and materials for MLE tool adoption.
  • Actively participate in cross-functional meetings and discussions, providing feedback, commentary, requirements, and questions to ensure alignment and drive project success.


Education and Experience


The below represents the primary duties of the position, others may be assigned as needed. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • Bachelor’s degree with 8 years of machine learning engineering or similar experience at software companies; or, advanced degree (master’s or PhD) in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or other quantitative field, with 3 years of demonstrated machine learning engineering success or similar experience.
  • Experience in building production-grade machine learning models and infrastructure in Python.
  • Strong background in advanced Python and big data technologies
  • Experience with cloud infrastructure (i.e., AWS, GCP, or Azure).
  • Demonstrated experience with Infrastructure as Code (IAC) tools (i.e. CDK, Pulumi, etc.).
  • Demonstrated ability to leverage machine learning engineering to drive business results.
  • Skilled at translating business problems into machine learning engineering problems and communicating the results to non-technical audiences.
  • Able to work in a collaborative environment with a desire to share your ideas.
  • Able to work independently and complete tasks with high quality, but unafraid to seek out suggestions from other team members.
  • Strong understanding of data engineering and software engineering fundamentals.
  • Self-motivated, adaptable, and highly detail oriented.


Preferred Skills

  • Professional or academic experience in HR, social science or psychology
  • Contributions to open-source software in Python
  • Enthusiastic about how machine learning and infrastructure can lead to a superior customer experience.
  • Be invested in staying current in machine learning and infrastructure by applying new technologies and practices. • Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
  • Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.


Physical requirements

  • Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
  • Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.

Paylocity is an equal-opportunity employer. Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.
We embrace and encourage our employees’ differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.

We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact accessibility@paylocity.com. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.

The base pay range for this position is $146,600 - $272,200 /yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. This position is eligible for an annual bonus and restricted stock unit grant based on individual performance in addition to a full range of benefits outlined here . This information is provided per the relevant state and local pay transparency laws for the location in which this position will be performed. Base pay information is based on market location. Applicants should apply via www.paylocity.com/careers.

Requirements:



What Paylocity employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom