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Machine Learning Engineer Quantization Jobs in Illinois

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126K - $166K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and operationalizing productiongrade AI solutions-partnering closely with product, engineering, and ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$107K - $147K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

PayPal

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

PayPal, Inc.

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

AppFolio

IL

$107K - $147K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Chicago, IL

$107K - $147K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

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Machine Learning Engineer Quantization information

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 Illinois? For Machine Learning Engineer Quantization jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Illinois look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Illinois are:
What cities in Illinois are hiring for Machine Learning Engineer Quantization jobs? Cities in Illinois with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer / Scientist

Until

Mundelein, IL • On-site

Full-time

Posted 12 days ago

Job description

Until is a moonshot company building a “pause button” for biology. Our near-term focus is organ-scale reversible cryopreservation: preserving donated organs at subzero temperatures without ice formation, then rewarming them uniformly for transplant. By solving this grand challenge, we’re laying the foundation for whole-body reversible cryopreservation, giving patients a bridge to future cures.

To achieve our goal, we are assembling an interdisciplinary team to develop perfusion systems, cryoprotectant formulations, and vitrification and rewarming hardware. We are also building out our medical hibernation team to tackle the challenges of whole-body cryopreservation, beginning with rodent models.

We envision a future where no transplantable organ is lost to logistics, and no terminal diagnosis is final because patients can safely wait for future medicine to arrive.

About the Role
As a Machine Learning Engineer / Scientist at Until, you will be an early member of the computational team defining how experimental data becomes insight and drives the next round of scientific discovery. You’ll build high-leverage ML systems that help develop new cryoprotectant formulations, engineer biologically-inspired antifreeze proteins, and understand the physics of vitrification and rewarming. You will own projects end-to-end including shaping data collection and designing data pipelines, training and evaluating models, and deploying tooling that scientists use daily. 
About You
  • Degree in Computer Science or a related field (Applied Mathematics, Statistics, Data Science, Computational Biology).
  • Excellent foundations in the mathematics that underlies machine learning, including linear algebra, probability, statistics, and calculus. 
  • Strong experience in modern machine learning approaches, such as representation learning, generative modeling, active learning, and bayesian optimization.
  • Track record of developing ML approaches for scientific discovery, as evidenced by a strong publication record, substantial open source contributions, or deployment of a machine learning system in an industry role.
  • Demonstrated ability to write modular, maintainable, and performant code in Python.
  • Fluency with the Python data science and ML stack, including PyTorch, NumPy, SciPy, Pandas/Polars, Matplotlib/Plotly.
  • Proficient with developer tooling, including Linux command line, Git, and shell scripting.
  • Ability to think from first principles and tackle complex, cross-disciplinary problems with other scientists and engineers.
Preferred Qualifications
  • 3+ years of relevant professional or research experience, or a PhD in a computational field.
  • Strong understanding of computer science fundamentals, including algorithms, operating systems, and concurrency. 
  • Experience with cloud infrastructure (AWS, GCP) and SQL databases.
Benefits
  • Opportunity for outsized impact creating the future as an early team member
  • Generous medical, dental and vision insurance coverage
  • Flexible time off and paid holidays
  • Competitive compensation package, including salary and equity
  • 401(k) retirement savings plan
  • FSA and commuter benefits
  • Subsidized lunch daily
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range. Please keep in mind that the equity portion of the offer is not included in this estimate.
As an equal opportunity employer, Until is committed to providing employment opportunities to all individuals. All applicants for positions at Until will be treated without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.