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Afternoon Full Stack Machine Learning Engineer Jobs in Chicago, IL

Gotion, Inc.

Machine Learning Engineer

Manteno, IL

We lead the full product development cycle, integrating mechanical, electrical, thermal, and ... Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ...

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

We lead the full product development cycle, integrating mechanical, electrical, thermal, and ... Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ...

Paylocity

Staff Machine Learning Engineer

Schaumburg, IL · On-site

Our machine learning engineering team is responsible for developing infrastructure and tooling to ... Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ... a full range of benefits outlined here. This information is provided per the relevant state and ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Our machine learning engineering team is responsible for developing infrastructure and tooling to ... a full range of benefits outlined here. This information is provided per the relevant state and ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ... Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and ...

PayPal, Inc.

Machine Learning Engineer

Chicago, IL · On-site

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 ...

PayPal

Machine Learning Engineer

Chicago, IL · On-site

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 ...

Apex Systems

Senior Machine Learning Engineer

Chicago, IL · On-site

$107K - $147K/yr

... full lifecycle of the product including data ingestion, ML processing, and results delivery ... respect to Machine Learning Engineering. Partner with data architecture, data governance, and ...

Referrals Only

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end ... For additional information, please see our full Thoughtworks AI Policy for Recruitment. EEO ...

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All JobsAfternoon Full Stack Machine Learning Engineer JobsAfternoon Full Stack Machine Learning Engineer Jobs in Chicago, IL

Afternoon Full Stack Machine Learning Engineer information

See Chicago, IL salary details

$45.8K

$138.8K

$196.2K

How much do afternoon full stack machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for afternoon full stack machine learning engineer in Chicago, IL is $138,833.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,300.00 and $162,800.00 per year, depending on experience, location, and employer.
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Afternoon Full Stack Machine Learning Engineer jobs near you

Machine Learning Engineer

Quantum Machines

Chicago, IL • On-site

Full-time

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

Job description

Description
Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions based on instruction-based quantum control, we're revolutionizing how quantum computers are built and controlled. As we stand at the forefront of exponential growth in quantum computing, we're assembling an elite team that actively shapes the evolution of quantum technologies.
We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.
You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.
Responsibilities:
  • Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
  • Develop real-time parameter steering for calibration during QEC and between circuits.
  • Develop and maintain agentic frameworks for autonomous system control and calibration.
  • Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
  • Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
  • Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

Requirements
  • PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
  • Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
  • Strong Python proficiency, including scientific or systems-oriented codebases
  • Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
  • Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
  • Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
  • Proven software development track record and excellent technical communication skills
  • Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
  • Experience with sim-to-real, multi-objective RL, or meta-learning- advantage

Apply