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Temporary Machine Learning Trainer Jobs in Wisconsin

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

What You Will Do: · Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining. · ...

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance ...

Hispanic Alliance for Career Enhancement

WI · On-site

$107 - $261/hr

Designs and implements scalable and efficient machine learning systems, including data pipelines, preprocessing, feature engineering, and model training, ensuring the quality and integrity of health ...

Marian Inc.

Machine Operator

Milwaukee, WI · On-site

$15 - $20/hr

THIS IS A TEMPORARY POSITION WITH THE INTENT TO HIRE FULL TIME WILLING TO PROVIDE TRAINING FLEXIBLE ... Mathematical, analytical, and mechanical skills are also essential to success as a machinist. Under ...

Verstela

Manufacturing Machine Operator

Franksville, WI · On-site

$18 - $21/hr

They offer a supportive team environment, hands-on training and the opportunity for long-term employment. In this temp-to-hire Manufacturing Machine Operator role, you'll learn how to operate ...

New

KOHLS

Data Scientist (Remote)

Menomonee Falls, WI · On-site

Develop and implement statistical and machine learning models to solve business problems within a ... training opportunities * Additional tasks may be assigned Addendum DECISION SCIENCE ...

A L SCHUTZMAN COMPANY

Roasting Machine Operator

Waukesha, WI

$17 - $20.25/hr

... or temporary staff. * Communicate with all coworkers including maintenance and quality staff to ... Must attend all company required training. What we have to offer you as an employee of AL Schutzman ...

Pwc

AI Engineer

Milwaukee, WI · On-site

$50K - $112K/yr

... training and/or progressively responsible work experience in Engineering with AI and Machine Learning for each missing year of college is required - At least 1 years of experience What Sets You Apart ...

micro1 AI

AI Trainer - Microbiology Expert

Madison, WI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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All JobsMachine Learning Trainer JobsTemporary Machine Learning Trainer JobsTemporary Machine Learning Trainer Jobs in Wisconsin

Temporary Machine Learning Trainer information

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 cities in Wisconsin are hiring for Temporary Machine Learning Trainer jobs?

Cities in Wisconsin with the most Temporary Machine Learning Trainer job openings:

Temporary Machine Learning Trainer jobs near you

Senior ML Ops Engineer

Paradigm

Middleton, WI • On-site

$123K - $170K/yr

Full-time

Re-posted 9 days ago

Job description

Paradigm is a software company transforming the way that the residential, construction & building product industries operate across the globe. We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first experiences. We are powered by our parent company, Builders FirstSource (NYSE: BLDR): a Fortune 300 company with over $23 billion in revenue and more than 29,000 employees across 550+ locations, BFS is redefining construction through data, digital infrastructure, and AI-powered innovation.

What You Will Do:

· Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining.

· Develop and optimize automated ML deployment pipelines, ensuring reliable, reproducible, and efficient model delivery to production environments.

· Deploy and support machine learning models and AI solutions in production, maintaining best practices for scalability, reliability, security, and operational excellence.

· Implement and maintain model registries, experiment tracking, versioning, and governance practices to support consistent model lifecycle management.

· Build and support containerized ML workloads and deployment workflows using technologies such as Docker and Kubernetes.

· Develop monitoring, observability, and alerting capabilities for machine learning systems, including model performance tracking, drift detection, and data quality monitoring.

· Collaborate with Machine Learning Engineers, Data Scientists, Software Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment efficiency.

· Implement and maintain IaC patterns using Terraform.

· Troubleshoot and resolve complex technical challenges related to model deployment, ML infrastructure, and production operations.

· Provide guidance and mentorship to other engineers.

What You Need to Succeed:

· Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or related field or equivalent experience.

· 4+ years of professional experience in software engineering, machine learning engineering, MLOps, platform engineering, DevOps, or a related technical discipline.

· Strong understanding of the machine learning lifecycle, including model training, validation, deployment, monitoring, and retraining.

· Experience building and maintaining automated machine learning pipelines and CI/CD workflows.

· Experience with MLOps platforms and tools such as MLflow, Kubeflow, Azure Machine Learning, Databricks, or similar technologies.

· Experience in Python programming, ML Framework and Agentic AI. Implemented model monitoring, experiment tracking, model versioning, and governance practices.

· Experience working with cloud-based machine learning solutions, preferably within Azure.

· Ability to independently solve complex technical challenges, make sound decisions with minimal guidance, and drive work to completion.

Ready to Join? Apply now at myparadigm.com/careers/

Compensation Range: $123K - $170K