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Temporary Machine Learning Trainer Jobs in Chicago, IL

Machine Learning Engineer

Chicago, IL · On-site

$62 - $100/hr

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure) Knowledge of ...

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.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training ...

Staff Machine Learning Engineer - Leasing

Chicago, IL · On-site

$17.50 - $20.50/hr

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and ... Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

Own endtoend LLM systems: architecture, training, evals, and iteration * Finetune 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

Showing results 41-60

Temporary Machine Learning Trainer information

See Chicago, IL salary details

$28.8K

$90K

$115.9K

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

As of Aug 23, 2026, the average yearly pay for temporary machine learning trainer in Chicago, IL is $89,957.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,800.00 and $114,300.00 per year, depending on experience, location, and employer.

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 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 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 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 are the most commonly searched types of Machine Learning Trainer jobs in Chicago, IL?

The most popular types of Machine Learning Trainer jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Temporary Machine Learning Trainer jobs?

Cities near Chicago, IL with the most Temporary Machine Learning Trainer job openings:

Senior Lead Machine Learning Engineer

Capital One

Chicago, IL • On-site

Full-time

Posted 14 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

93rd of 171 rated banks


Job description

Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What You'll Do:
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
  • Retrain, maintain, and monitor models in production
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
  • Use programming languages like Python, Scala, or Java

Basic Qualifications:
  • Bachelor's Degree
  • At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 3 years of experience building, scaling, and optimizing ML systems
  • At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications:
  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
  • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
  • 3+ years of experience developing performant, resilient, and maintainable code
  • 3+ years of experience with data gathering and preparation for ML models
  • 3+ years of people management experience
  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
  • 3+ years of experience building production-ready data pipelines that feed ML models
  • Ability to communicate complex technical concepts clearly to a variety of audiences
  • Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Chicago, IL: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer
McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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