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Phd Machine Learning Startup Jobs in Illinois (NOW HIRING)

Quantum Machines

Machine Learning Engineer

Chicago, IL · On-site

Required : • 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 ...

New

Coin Flow

Machine Learning Engineer

Chicago, IL

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers ... Experience as an early data/ML hire at a startup * Experience working with high-volume behavioral ...

Coinflow

Machine Learning Engineer

Chicago, IL · On-site

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers ... Experience as an early data/ML hire at a startup * Experience working with high-volume behavioral ...

IMC Trading

Machine Learning Researcher

Chicago, IL · On-site

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : • PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

IMC

Machine Learning Researcher

Chicago, IL

Design and deploy machine learning models to enhance trading performance across various asset ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

... Required Qualifications PhD (preferred) or Master's degree in Computer Science, Electrical ... startup environment Extensive use of AI tools for coding, optimization, and ideation Preferred ...

IMC

Machine Learning Research Lead

Chicago, IL

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

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Phd Machine Learning Startup information

What are some common challenges faced by PhD-level professionals working in machine learning startups?

PhD-level professionals in machine learning startups often encounter challenges such as balancing research innovation with the need for rapid product development. Unlike academia, startups prioritize practical solutions that fit tight deadlines and resource constraints. Team members typically wear multiple hats and collaborate closely with engineers, product managers, and business stakeholders, requiring strong communication skills and adaptability. Additionally, translating cutting-edge research into scalable, real-world applications can be both intellectually rewarding and demanding.

What do PhD holders in Machine Learning do at startups?

PhD holders in Machine Learning at startups typically lead research and development efforts to create innovative algorithms and models that solve real-world problems. They often work on designing and implementing advanced machine learning solutions, analyzing large datasets, and collaborating with product and engineering teams to bring research ideas to production. Their expertise helps startups stay competitive by driving technological advancements and fostering a culture of innovation.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional in a startup environment, and why are they important?

To excel as a PhD-level Machine Learning professional at a startup, you need advanced expertise in machine learning algorithms, statistical modeling, and a doctoral degree in a related field. Experience with Python, TensorFlow, PyTorch, and version control systems, along with a strong publication record, is typically expected. Initiative, adaptability, and excellent problem-solving and communication abilities are crucial soft skills in the fast-paced startup setting. These competencies enable rapid innovation, effective team collaboration, and successful deployment of machine learning solutions under resource constraints.
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Phd Machine Learning Startup jobs near you

Machine Learning Engineer

Quantum Machines

Chicago, IL • On-site

Full-time

Posted 2 days ago

Job description

Job Summary:
Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors. The role involves developing ML solutions that enhance the calibration, control, and operation of quantum technologies, working at the intersection of machine learning and quantum physics.
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.
Qualifications:
Required:
• 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
Preferred:
• 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
Company:
Quantum Machines is a leading provider of quantum control solutions, powering quantum-classical integration at scale with Hybrid Control. Founded in 2018, the company is headquartered in Claymont, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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