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Temporary Machine Learning Trainer Jobs in Illinois

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ... or training. Your recruiter can share more about the specific salary range for your preferred ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ... or training. Your recruiter can share more about the specific salary range for your preferred ...

Machine Learning Tutor

Oak Lawn, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Evanston, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Skokie, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Normal, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Chicago, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Dekalb, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Wheaton, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Schaumburg, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Naperville, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Champaign, IL · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Temporary Machine Learning Trainer information

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 are Temporary Machine Learning Trainers?

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 the most commonly searched types of Machine Learning Trainer jobs in Illinois? The most popular types of Machine Learning Trainer jobs in Illinois are:
What cities in Illinois are hiring for Temporary Machine Learning Trainer jobs? Cities in Illinois with the most Temporary Machine Learning Trainer job openings:
Machine Learning Engineer

Machine Learning Engineer

Gotion, Inc.

Manteno, IL

Other

Posted 7 days ago


Job description

About The Team
The Product Development Team at Gotion Illinois New Energy Inc. focuses on the design and development of advanced battery products for next-generation energy storage system (ESS) and electric vehicle (EV) applications. We lead the full product development cycle, integrating mechanical, electrical, thermal, and control system to create high-performance battery solutions, along with comprehensive system integration, validation, and certification activities.

Role Summary

We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains such as battery technology, energy systems, or related physical sciences. This is a fully on-site role based in Manteno, IL focused on building innovative ML models from the ground up.

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine learning solutions that address real-world challenges in advanced materials, electrochemical systems, and high-throughput data environments.

Essential Duties and Responsibilities:

  • Design and implement novel machine learning and deep learning models tailored to internal research needs
  • Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures
  • Conduct rigorous experimentation, benchmarking, and ablation studies
  • Collaborate with battery scientists and domain experts to incorporate physical constraints or scientific priors into modeling
  • Contribute to internal documentation and present research outcomes to technical and leadership teams
  • Track and integrate advances from the ML research community to ensure technical excellence

Required Qualifications:

  • Ph.D. (preferred) or M.S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field
  • Demonstrated expertise in model development, optimization, and algorithmic innovation
  • Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc.
  • Solid understanding of learning theory concepts such as regularization, generalization, loss functions, and evaluation metrics
  • Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains, is highly desirable
  • A publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR) is a strong plus
  • Excellent communication, collaboration, and problem-solving skills in interdisciplinary environments

The US base salary range for this full-time position is $80,000.00 - $90,000.00 + 15% bonus + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.  Â