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Independent Contractor Aws Machine Learning Jobs in Springfield, IL

Bespoke Labs

Machine Learning Engineer

Springfield, IL · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Photon

Scrum Master- Springfield

Springfield, IL · On-site

$51 - $68.25/hr

Lead the implementation and optimization of Vertex AI solutions for advanced machine learning and ... Experience with other cloud platforms like AWS or Azure. * Knowledge of infrastructure as code (IaC ...

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Independent Contractor Aws Machine Learning information

See Springfield, IL salary details

$390

$1.1K

$2.1K

How much do independent contractor aws machine learning jobs pay per week?

As of Jun 26, 2026, the average weekly pay for independent contractor aws machine learning in Springfield, IL is $1,079.63, according to ZipRecruiter salary data. Most workers in this role earn between $715.38 and $1,200.00 per week, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Independent Contractor AWS Machine Learning Specialist, and why are they important?

To thrive as an Independent Contractor AWS Machine Learning Specialist, you need expertise in machine learning algorithms, data analysis, and proficiency with Python, as well as a strong understanding of AWS services like SageMaker and Lambda. Familiarity with cloud-based ML tools, experience with data pipelines, and AWS certifications such as AWS Certified Machine Learning – Specialty are highly valued. Exceptional problem-solving, communication, and project management skills help you collaborate with clients and deliver solutions efficiently. These skills ensure you can design, implement, and optimize machine learning models in scalable cloud environments, meeting diverse client needs.

What does an Independent Contractor specializing in AWS Machine Learning do?

An Independent Contractor specializing in AWS Machine Learning works on a freelance or contract basis to design, develop, and deploy machine learning solutions using Amazon Web Services. They may help clients with data preparation, model training, and integration of machine learning models into existing systems using AWS tools like SageMaker, Lambda, and S3. Their responsibilities often include consulting on best practices, optimizing workflows, and ensuring scalable, secure machine learning infrastructures in the cloud.

What is the difference between Independent Contractor Aws Machine Learning vs Data Scientist?

AspectIndependent Contractor Aws Machine LearningData Scientist
CredentialsCertifications in AWS, Machine Learning, and cloud computingDegree in Data Science, Statistics, or related field; often certifications like SAS or Python
Work EnvironmentFreelance, project-based, remote or on-site in cloud environmentsFull-time, corporate or research settings, often in office or remote
Employer & IndustryClients across various industries using AWS cloud servicesOrganizations in tech, finance, healthcare, and research sectors

While both roles involve data analysis and machine learning, an Independent Contractor Aws Machine Learning specializes in deploying models on AWS cloud platforms as a freelancer, whereas a Data Scientist typically works within organizations analyzing data and building models in a more permanent role.

What are some common challenges faced by independent contractors working on AWS Machine Learning projects, and how can they be managed?

Independent contractors in AWS Machine Learning often face challenges such as staying updated with rapidly evolving AWS services, managing project scope with limited resources, and ensuring data security and compliance. To address these, it's important to regularly participate in AWS training, maintain clear communication with clients about project expectations, and follow best practices for security and data handling. Proactively setting up efficient workflows and leveraging AWS documentation and community forums can also help manage technical and logistical hurdles.
What job categories do people searching Independent Contractor Aws Machine Learning jobs in Springfield, IL look for? The top searched job categories for Independent Contractor Aws Machine Learning jobs in Springfield, IL are:
What cities near Springfield, IL are hiring for Independent Contractor Aws Machine Learning jobs? Cities near Springfield, IL with the most Independent Contractor Aws Machine Learning job openings:
Independent Contractor Aws Machine Learning jobs near you
Infographic showing various Independent Contractor Aws Machine Learning job openings in Springfield, IL as of June 2026, with employment types broken down into 74% Full Time, 20% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $56,141 per year, or $27 per hour.

Machine Learning Engineer

Bespoke Labs

Springfield, IL • On-site

Full-time

Posted 9 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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