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Temporary Machine Learning Trainer Jobs in Geneva, IL

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Senior AI Machine Learning Engineer

Chicago, IL · On-site

$126K - $166K/yr

The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ... Develop and operate batch and near-real-time data/AI pipelines for model training, feature ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

Own end-to-end LLM systems: architecture, training, evals, and iteration * Fine-tune and extend ... Equipment and learning budget to help you do your best work and keep up with the frontier

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

You will: * Own end‑to‑end LLM systems: architecture, training, evals, and iteration ... Equipment and learning budget to help you do your best work and keep up with the frontier

Model Training and Deployment: Train, test, and tune machine learning models, ensuring they meet quality standards and deploying them into production environments. * Performance Monitoring and ...

Showing results 41-60

Temporary Machine Learning Trainer information

See Geneva, IL salary details

$27.3K

$85.2K

$109.8K

How much do temporary machine learning trainer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for temporary machine learning trainer in Geneva, IL is $85,226.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $108,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a temporary machine learning trainer, and why are they important?

To thrive as a Temporary Machine Learning Trainer, you need a solid background in machine learning concepts, data analysis, and model evaluation, usually supported by a relevant degree or experience in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or scikit-learn), and educational tools is typically required. Strong communication, adaptability, and instructional skills help trainers effectively convey complex topics and respond to diverse learner needs. These skills ensure trainees gain practical knowledge and confidence, contributing to successful training outcomes and organizational goals.

What are some common challenges faced by temporary machine learning trainers, and how can they be managed effectively?

Temporary Machine Learning Trainers often face the challenge of quickly adapting to new team environments and rapidly understanding existing workflows. Additionally, they may need to balance delivering training sessions with handling updates to curriculum or technology. Effective communication with permanent staff and staying up-to-date with the latest machine learning tools can help manage these challenges. Being proactive in seeking feedback and clarifying expectations early on can also contribute to a smoother transition and more impactful training sessions.

What is the difference between Temporary Machine Learning Trainer vs Data Scientist?

AspectTemporary Machine Learning TrainerData Scientist
CredentialsRelevant certifications (e.g., AWS, Google Cloud), technical trainingAdvanced degrees (Master's or PhD) in data science, statistics, or related fields
Work EnvironmentTraining sessions, workshops, corporate training settingsData analysis, modeling, research environments, often in offices or labs
Employer & Industry UsageTech companies, educational institutions, consulting firmsTech, finance, healthcare, research organizations

While both roles involve working with data and machine learning, a Temporary Machine Learning Trainer primarily focuses on educating and training teams or clients on machine learning tools and concepts. In contrast, a Data Scientist develops models, analyzes data, and derives insights for decision-making. The roles differ mainly in their focus—training versus data analysis—though they share foundational technical skills.

What is a temporary machine learning trainer?

Temporary Machine Learning Trainers are professionals hired on a short-term or contract basis to develop, implement, and refine machine learning models or to train teams in machine learning techniques. Their responsibilities often include preparing training data, selecting appropriate algorithms, and ensuring models are accurate and efficient. They may also provide guidance to organizations on best practices and help upskill employees in machine learning concepts. These roles are typically project-based and may last from a few weeks to several months, depending on organizational needs.
What cities near Geneva, IL are hiring for Temporary Machine Learning Trainer jobs? Cities near Geneva, IL with the most Temporary Machine Learning Trainer job openings:

Sr. Machine Learning Engineer (Canada - Remote)

Hyatt Hotels Corporation

Chicago, IL • On-site, Remote

$126K - $166K/yr

Full-time

Medical, PTO

Posted yesterday

New


Hyatt Hotels rating

7.1

Company rating: 7.1 out of 10

Based on 255 frontline employees who took The Breakroom Quiz

25th of 108 rated hotels


Job description

Summary:
The Opportunity
Hyatt Hotels Corporation seeks an enthusiastic Senior ML Engineer to join our Data Science and Machine Learning department. In this role, you will be collaborating closely with the broader Data and Analytics team, where you'll be instrumental in continuing to make Hyatt a leading hospitality company. You will be part of a team that is passionate about our purpose, committed to nurturing curiosity and new skills, and building connections across the organization with colleagues, customers, and guests.
Who We Are
At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957, our colleagues and our guests have been at the heart of our business and helped Hyatt become one of the best and fastest-growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands, and business lines can open the door for exciting career and growth opportunities for our colleagues.
As we continue to grow, we never lose sight of what's most important: People. We turn trips into journeys, encounters into experiences, and jobs into careers.
Why Now?
This is an exciting time to be at Hyatt. We are growing rapidly and are looking for passionate changemakers to be a part of our journey. The hospitality industry is resilient and continues to offer dynamic opportunities for upward mobility, and Hyatt is no exception.
How We Care for Our People
What sets us apart is our purpose-to care for people so they can be their best. Every business decision is made through the lens of our purpose, and it informs how we have and will continue to support each other as members of the Hyatt family. Our care for our colleagues is the key to our success. We're proud to have earned a place on Fortune's prestigious 100 Best Companies to Work For® list since 2013. This recognition is a testament to the tremendous way our Hyatt family continues to come together to care for one another, our commitment to a culture of inclusivity, empathy, and respect, and making sure everyone feels like they belong.
We're proud to offer exceptional corporate benefits which include:
• Annual allotment of free hotel stays at Hyatt hotels globally
• Flexible work schedule
• A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption
• Extended Health Benefits for you and your dependents and paid medical days
• Employer RRSP Matching Contributions
• Fitness and Wellness Allowance
• Cell Phone Allowance
Who You Are
As our ideal candidate, you understand the power and purpose of our culture of care, and embody our core values of Empathy, Inclusion, Integrity, Experimentation, Respect, and Wellbeing. You enjoy working with others, are results-driven, and are looking for a variety of opportunities to develop personally and professionally.
The Role
The Machine Learning Engineer partners with data science, data engineering, and platform teams to design, build, and operate scalable AI services. This role is responsible for translating machine learning models into reliable, production-grade systems through strong infrastructure design, MLOps automation, and performance optimization. The position also contributes to cross-functional initiatives that advance the organization's AI platform capabilities.
Responsibilities
• Design and implement end-to-end ML systems, including data ingestion, feature processing, model training, and model serving
• Architect and deploy scalable AI services supporting real-time and batch inference use cases
• Build and maintain ML infrastructure across cloud environments (e.g., EC2, EKS, SageMaker, specialized inference hardware)
• Develop and evolve MLOps platforms, including training pipelines, deployment workflows, feature stores, and model observability
• Implement CI/CD and infrastructure-as-code patterns to automate model lifecycle management
• Optimize model training and inference performance for cost, latency, and hardware efficiency
• Monitor production ML systems for accuracy, reliability, and operational health
• Partner cross-functionally with data engineering, architecture, governance, and security teams to ensure compliant and scalable solutions
• Mentor team members on ML engineering, system design, and operational best practices
• Contribute to special initiatives that advance AI platform maturity and engineering standards
Qualifications:
Experience Required:
• Master's degree in Computer Science, Software Engineering, Machine Learning, or a related field
• 5+ years of experience building and operating machine learning solutions in cloud environments, with focus on AI services and MLOps foundations
• Demonstrated hands-on experience delivering end-to-end ML systems, spanning model development, deployment, and production infrastructure
• Proficiency with modern ML engineering tooling, including cloud platforms, data pipelines, and CI/CD workflows
Experience Preferred
• Experience designing and scaling real-time and batch inference systems in production
• Hands-on experience with deep learning frameworks and model optimization for performance and cost
• Experience building or contributing to shared MLOps platforms, feature stores, or ML observability solutions
• Familiarity with cloud security, governance, and compliance standards
The position responsibilities outlined above are in no way to be construed as all-encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.
We welcome you:
Research shows that individuals tend to apply to jobs only if they meet all the listed job qualifications. Unsure if you check every box, but feeling inspired to enhance your career? Apply. We'd love to consider your unique experiences and how you could make Hyatt even better.
We value our relationships with recruitment partners and require that agencies contact us first before submitting any candidates. Hyatt will not be responsible for any fees and obligations associated with unsolicited submissions unless a formal agreement is in place.
ThesalaryrangeforthispositionisCAD90,000 - CAD110,000.Thispositionisalsoeligibletoearnanannualbonus.
Thefinalpayrate/salaryofferedtothesuccessfulcandidatewilldependonexperience,skilllevelandotherqualificationsfortherole,aswellasthelocationoftheperformanceofwork.Payforthesuccessfulcandidatewillmeetlocalrequirements,includingthelocalminimumwagerate.
Candidates must be legally authorized to work in Canada at the time of application and throughout their employment. Proof of eligibility to work in Canada will be required. Unless otherwise indicated in the job posting, Hyatt does not sponsor employment visas or work permits for this position. Applications from candidates who do not meet these requirements will not be considered.
Hyatt is committed to providing an inclusive and accessible recruitment experience. In accordance with applicable human rights and accessibility legislation across Canada, accommodation is available throughout the recruitment and selection process. If you require accommodation at any stage, please notify Human Resources, and we will work with you to meet your accessibility needs.

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About Hyatt

Sourced by ZipRecruiter

At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957, our colleagues and our guests have been at the heart of our business and helped Hyatt become one of the best, and fastest-growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands, and business lines can open the door for exciting career and growth opportunities for our colleagues. As we continue to grow, we never lose sight of what's most important: People. We turn trips into journeys, encounters into experiences, and jobs into careers.

Industry

Hospitality services

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1957