ZipRecruiter

Log In

1

New Grad Machine Learning Jobs in Carol Stream, IL

Unchain Data

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns ... in machine learning, applied data science, or production ML roles * Demonstrated experience ...

Coinflow

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns ... in machine learning, applied data science, or production ML roles * Demonstrated experience ...

SOLANA FOUNDATION

Machine Learning Lead

Chicago, IL · On-site

$175K - $235K/yr

Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns ... in machine learning, applied data science, or production ML roles * Demonstrated experience ...

Socket.dev

Machine Learning Engineer

Chicago, IL · On-site

Identify new areas where platform improvements, automation, and MLOps tooling can improve product ... a Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist or similar ...

Crowe Advisory LLC

Machine Learning Engineer

Chicago, IL · On-site

$62K - $100K/yr

About the Role As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves ...

previous page

Showing results 41-60

All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Carol Stream, IL

New Grad Machine Learning information

See Carol Stream, IL salary details

$26.4K

$44K

$91K

How much do new grad machine learning jobs pay per year?

As of Sep 12, 2026, the average yearly pay for new grad machine learning in Carol Stream, IL is $44,044.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,600.00 and $47,600.00 per year, depending on experience, location, and employer.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What job categories do people searching New Grad Machine Learning jobs in Carol Stream, IL look for?

The top searched job categories for New Grad Machine Learning jobs in Carol Stream, IL are:

What cities near Carol Stream, IL are hiring for New Grad Machine Learning jobs?

Cities near Carol Stream, IL with the most New Grad Machine Learning job openings:

New Grad Machine Learning jobs near you
Infographic showing various New Grad Machine Learning job openings in Carol Stream, IL as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,044 per year, or $21.2 per hour.

Emerging Technology Solutions Architect - Machine Learning

Chicago, IL • On-site

US Bank
Banking and Credit Intermediation • 10K+ employees
Learn more about US Bankexternal

$65 - $85.50/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago

Key responsibilities

  • Evaluate emerging machine learning technologies, platforms, frameworks, and tooling ecosystems for enterprise adoption.

  • Define scalable architectures supporting the end-to-end machine learning lifecycle, including data ingestion, feature engineering, model training, deployment, monitoring, and governance.

  • Partner with data scientists and engineering teams to operationalize machine learning models at scale.

U.S. Bank rating

8.1

Company rating: 8.1 out of 10

Based on 364 frontline employees who took The Breakroom Quiz

Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

U.S. Bank is seeking an Emerging Technology Solutions Architect - Machine Learning to evaluate, design, and guide adoption of machine learning technologies across the enterprise. This role focuses on identifying emerging ML capabilities, assessing enterprise fit, and defining scalable solutions that enable advanced analytics, predictive modeling, and AI-driven business outcomes while aligning to enterprise standards.

The Emerging Technology Solutions Architect will partner across data engineering, platform engineering, data science, and risk/security teams to evaluate technologies, define architecture patterns, and enable implementation through strong technical leadership and hands-on solution design. This role will help shape the future of machine learning capabilities at U.S. Bank by establishing scalable, secure, and reusable solutions that accelerate responsible innovation.

Responsibilities
  • Evaluate emerging machine learning technologies, platforms, frameworks, and tooling ecosystems for enterprise adoption.
  • Assess ML technologies and services including Azure Machine Learning, AWS SageMaker, Databricks, Snowflake ML, and open-source ML frameworks.
  • Define scalable architectures supporting the end-to-end machine learning lifecycle, including data ingestion, feature engineering, model training, deployment, monitoring, and governance.
  • Recommend architecture patterns based on performance, scalability, security, explainability, and operational risk requirements.
  • Establish reusable solution patterns for MLOps, model serving, feature stores, automated retraining, model monitoring, and observability.
  • Design and recommend production-ready machine learning solutions with sufficient technical depth to support engineering and data science teams through implementation.
  • Evaluate vendor platforms and ecosystem offerings for enterprise fit, long-term viability, and business value.
  • Partner with data scientists and engineering teams to operationalize machine learning models at scale.
  • Provide technical leadership on machine learning architecture, MLOps, model lifecycle management, and production deployment strategies.
  • Establish standards and best practices for model governance, observability, explainability, and responsible AI.
  • Translate complex technical concepts into clear recommendations for technical and non-technical stakeholders.
  • Assess emerging machine learning technologies and translate exploratory findings into enterprise-ready recommendations.
Basic Qualifications
  • Bachelor's degree or equivalent work experience.
  • Eight (8) or more years of experience in software engineering, machine learning engineering, data engineering, solution architecture, or related technical roles.
Preferred Skills / Experience
  • Strong foundation in machine learning, software engineering, and solution architecture.
  • Experience designing and deploying production machine learning systems in cloud environments.
  • Expertise in MLOps practices, including CI/CD pipelines, model versioning, monitoring, governance, and automated retraining.
  • Hands-on experience with machine learning platforms such as Azure Machine Learning, AWS SageMaker, Databricks, Snowflake ML, MLflow, or Kubeflow.
  • Knowledge of machine learning frameworks including PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar technologies.
  • Experience architecting solutions involving feature stores, model serving, real-time inference, batch scoring, and machine learning pipelines.
  • Understanding of machine learning concepts including supervised learning, unsupervised learning, forecasting, recommendation systems, anomaly detection, and model explainability.
  • Experience making architecture decisions grounded in real-world tradeoffs including cost, performance, scalability, security, governance, and model accuracy.
  • Ability to design solutions and provide technical guidance through implementation, not purely conceptual architecture.
  • Strong communication, stakeholder alignment, and cross-functional leadership skills.
  • Familiarity with generative AI and large language models is preferred but not required.
Location Expectation

This role requires working from a U.S. Bank location three (3) or more days per week.

If there's anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to ourdisability accommodations for applicants.

Benefits:

Our approach to benefits and total rewards considers our team members' whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following:

  • Healthcare (medical, dental, vision)

  • Basic term and optional term life insurance

  • Short-term and long-term disability

  • Pregnancy disability and parental leave

  • 401(k) and employer-funded retirement plan

  • Paid vacation (from two to five weeks depending on salary grade and tenure)

  • Up to 11 paid holiday opportunities

  • Adoption assistance

  • Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Review our full benefits available by employment status here.

U.S. Bank is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and other factors protected under applicable law.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about theE-Verify program.

The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $139,230.00 - $163,800.00

U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures.

Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.

Posting may be closed earlier due to high volume of applicants.

What U.S. Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

U.S. Bank logo

About U.S. Bank

Sourced by ZipRecruiter

U.S. Bank is a reputable and established financial institution that plays a significant role in the banking sector. With a history spanning over 150 years, U.S. Bank has built a strong foundation of trust and reliability. As a comprehensive bank, they offer a wide array of financial products and services to cater to the diverse needs of their customers, including individuals, businesses, and communities. Customer satisfaction is of utmost importance to U.S. Bank. They prioritize delivering exceptional service and fostering long-term relationships with their clients. Through their extensive network of branches and advanced digital banking platforms, U.S. Bank ensures convenient access to their services, empowering customers to manage their finances efficiently and securely.

Industry

Banking and credit intermediation

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

Year founded

1863

Social media

FacebookTwitter

View All U.S. Bank Jobs

Apply