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Machine Learning Engineer Jobs in Niles, IL (NOW HIRING)

Sr Machine Learning Engineer

Chicago, IL

$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 ...

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

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 ...

AI & Machine Learning Engineer

Chicago, IL

$118K - $141.80K/yr

... machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on ...

AI & Machine Learning Engineer

Chicago, IL

$118K - $141.80K/yr

... machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on ...

Sr AI Machine Learning Engineer

Chicago, IL · On-site

$117.20K - $175.80K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126.20K - $166.40K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126.20K - $166.40K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and offsites * Equipment and learning budget to help you do your best work and keep up with the ...

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Machine Learning Engineer information

See Niles, IL salary details

$31.7K

$129.5K

$194.5K

How much do machine learning engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning engineer in Niles, IL is $129,458.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,000.00 and $155,800.00 per year, depending on experience, location, and employer.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Niles, IL? The most popular types of Machine Learning Engineer jobs in Niles, IL are:
What are popular job titles related to Machine Learning Engineer jobs in Niles, IL? For Machine Learning Engineer jobs in Niles, IL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Niles, IL look for? The top searched job categories for Machine Learning Engineer jobs in Niles, IL are:
What cities near Niles, IL are hiring for Machine Learning Engineer jobs? Cities near Niles, IL with the most Machine Learning Engineer job openings:
Sr Machine Learning Engineer

Sr Machine Learning Engineer

PayPal

Chicago, IL

$57.50 - $76/hr

Full-time

Medical, PTO

Posted 11 days ago


PayPal rating

6.8

Company rating: 6.8 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

15th of 17 rated payment service providers


Job description

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

This job is responsible for independently validating and providing oversight of high-impact statistical, machine learning, and AI models across key business areas such as credit, fraud, marketing, and collections. It involves assessing model soundness, data quality, and performance to identify and mitigate model risk, while collaborating with developers and business partners on remediation and improvement. The position also supports AI and model risk governance to ensure compliance with PayPal's enterprise risk framework and evolving regulatory standards.

Job Description:

Essential Responsibilities:

  • Develop and optimize machine learning models for various applications.
  • Preprocess and analyze large datasets to extract meaningful insights.
  • Deploy ML solutions into production environments using appropriate tools and frameworks.
  • Collaborate with cross-functional teams to integrate ML models into products and services.
  • Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

  • 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
  • Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
  • Several years of experience in designing, implementing, and deploying machine learning models.

Additional Responsibilities & Preferred Qualifications:

  • Advanced degree (Master's or Ph.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 not limited to logistic regression, time-series modeling, random forests, support vector machines, gradient boosting (e.g., XGBoost), and deep learning architectures (e.g., CNNs, RNNs).
  • Proficiency in programming and big-data technologies, with hands-on experience in tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and Spark.
  • Relevant modeling experience in one or more of the following domains: credit risk scoring, fraud detection, financial forecasting, or marketing analytics - gained through industry or academic research.
  • Strong collaboration and communication skills, with the ability to work effectively both independently and as part of a cross-functional team.
  • Ability to articulate complex technical concepts clearly to non-technical stakeholders and build constructive working relationships across functions.

Preferred Qualifications

  • Experience with Large Language Models (LLMs), Agentic AI, or related generative AI applications.
  • Familiarity with model governance, model risk management, or AI regulatory compliance frameworks (e.g., SR 11-7, OCC 2011-12, EU AI Act) is a plus.

Subsidiary:

PayPal

Travel Percent:

0

-

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

Chicago, Illinois | ($145,000.00 - $215,050.00 Annually)

Additional Location(s) | Pay Range:

San Jose, California | ($159,500.00 - $236,500.00 Annually) Austin, Texas | ($145,000.00 - $215,050.00 Annually) Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most.We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

Who We Are:

Click Here to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.


What PayPal employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


PayPal logo

About PayPal

Sourced by ZipRecruiter

PayPal has remained at the forefront of the digital payment revolution for more than 20 years. By leveraging technology to make financial services and commerce more convenient, affordable, and secure, the PayPal platform is empowering more than 400 million consumers and merchants in more than 200 markets to join and thrive in the global economy. For more information, visit paypal.com. PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1998

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