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Weekday Machine Learning Research Scientist Jobs in Elgin, IL

Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models. * Experience with generative AI technologies, including LLMs, fine-tuning, RAG ...

D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Mathematics, Statistics, or a related technical discipline. * 8+ years of experience in AI/ML research ...

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

The Machine Learning Researcher should be interested in Financial Markets, and will be directly involved in advancing the company's Data Analysis and Machine Learning capabilities. They'll be working ...

New

We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your ...

Showing results 21-40

Weekday Machine Learning Research Scientist information

See Elgin, IL salary details

$49.9K

$128.6K

$172K

How much do weekday machine learning research scientist jobs pay per year?

As of Aug 7, 2026, the average yearly pay for weekday machine learning research scientist in Elgin, IL is $128,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $171,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

What cities near Elgin, IL are hiring for Weekday Machine Learning Research Scientist jobs? Cities near Elgin, IL with the most Weekday Machine Learning Research Scientist job openings:

AI Research Scientist

US Bank

Chicago, IL • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


U.S. Bank rating

8.2

Company rating: 8.2 out of 10

Based on 360 frontline employees who took The Breakroom Quiz

51st of 170 rated banks


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 AI Scientist to join the Artificial Intelligence Center of Excellence (AI CoE), a high-impact organization responsible for advancing the bank's AI strategy through applied research, innovation, rapid prototyping, and enterprise deployment.

This role is ideal for a highly technical and hands-on AI practitioner who thrives at the intersection of research, experimentation, and implementation. The successful candidate will continuously evaluate emerging advances in artificial intelligence, identify opportunities to create business value, rapidly prototype novel solutions, and help evolve successful concepts into scalable enterprise capabilities.

Unlike traditional data science roles, this position spans the full AI research and development lifecycle. The ideal candidate combines strong scientific and engineering expertise with a practical mindset, enabling them to move seamlessly from exploratory research and experimentation to the development and deployment of production-grade AI solutions.

The candidate is expected to remain actively engaged with the broader AI community, stay current on academic and industry developments, and contribute to advancing AI innovation within the bank.

Key ResponsibilitiesAI Research & Innovation
  • Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems.

  • Identify opportunities to apply advanced AI techniques to complex business problems across financial services.

  • Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches.

  • Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and business stakeholders.

  • Contribute to patents, technical publications, whitepapers, prototypes, and innovation initiatives.

Prototyping & Solution Development
  • Rapidly transform research concepts into working prototypes and proof-of-concepts.

  • Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring.

  • Build experimental and production-ready solutions using modern AI/ML tools, frameworks, and cloud platforms.

  • Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.

Generative AI & Agentic Systems
  • Develop solutions leveraging foundation models, generative AI, retrieval-augmented generation (RAG), fine-tuning techniques, and agentic workflows.

  • Design and evaluate AI agents, multi-agent systems, orchestration frameworks, tool-use architectures, memory systems, and human-in-the-loop workflows.

  • Contribute to best practices for prompt engineering, model adaptation, evaluation, observability, and governance of LLM-based systems.

  • Assess emerging model architectures and determine their applicability within a highly regulated environment.

Deployment & Technical Collaboration
  • Partner with software engineers, platform teams, product managers, and business stakeholders to transition successful prototypes into production environments.

  • Contribute to deployment and operationalization efforts for AI solutions.

  • Help balance innovation, scalability, security, compliance, and operational requirements throughout solution development.

  • Share knowledge and provide technical guidance to peers and junior team members.

  • Take ownership of assigned initiatives and ensure successful delivery of AI capabilities from concept through deployment.

Basic Qualifications

  • Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience
  • Eight or more years of relevant experience
Preferred Qualifications
  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Linguistics, or a related field strongly preferred.

  • Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.

  • Experience with generative AI technologies, including LLMs, fine-tuning, RAG systems, model evaluation, and inference optimization.

  • Experience building and evaluating agentic AI systems, multi-agent workflows, AI orchestration frameworks, and autonomous decision-making architectures.

  • Hands-on experience with PyTorch, Hugging Face, LangChain, LangGraph, or equivalent AI ecosystems.

  • Demonstrated record of innovation through publications, patents, open-source contributions, conference presentations, or impactful AI solution delivery.

  • Experience developing AI solutions within highly regulated industries such as financial services, healthcare, insurance, or telecommunications.

  • Strong communication skills and the ability to translate complex AI concepts into actionable business outcomes.

**The role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.**

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: $133,365.00 - $156,900.00

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

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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

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