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Temporary Machine Learning Trainer Jobs in Illinois

Bespoke Labs

Machine Learning Engineer

Peoria, IL

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Dekalb, IL

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Referrals Only

Lead Machine Learning Engineer

Chicago, IL

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end ... model training and deployment, and monitoring and evaluation. * As a key influencer, you will ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Build ML data pipelines from sensor acquisition through model training and deployment * Establish ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

... training and deployment • Establish data labeling, versioning, and management workflows for ... Machine Learning, Computer Science, Robotics, or related field • Experience with robotics ...

Until

Machine Learning Engineer / Scientist

Mundelein, IL

$140K - $240K/yr

About the Role As a Machine Learning Engineer / Scientist at Until, you will be an early member of ... training and evaluating models, and deploying tooling that scientists use daily. About You * Degree ...

Quora

$139K - $168K/yr

Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and training, to realtime LLM application at scale Minimum Requirements: * Ability to be available for ...

Quora

$139K - $168K/yr

Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and training, to realtime LLM application at scale Minimum Requirements: * Ability to be available for ...

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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 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 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:
Temporary Machine Learning Trainer jobs near you

Machine Learning Engineer

Bespoke Labs

Peoria, IL

Full-time

Re-posted 21 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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