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Ai Optimization Jobs in Wisconsin (NOW HIRING)

Pwc

AI Engineer

Milwaukee, WI · On-site

$50K - $112K/yr

... Optimizing open-weight language models, including LLaMA, Mistral, and Gemma, for local and cloud ... for AI projects - Utilizing machine learning libraries like Scikit-Learn for data analysis ...

GoStudent

Bei brutal.ai, einem Spin-off von GoStudent, gestaltest du die Zukunft ganzer Branchen mit ... B. für Restaurants von Website & SEO bis hin zu Delivery, Reviews und Loyalty, morgen für viele ...

AgSource

AI Engineer

Watertown, WI · On-site +1

Sometimes it's optimization, classical statistics or generative AI. We want someone with the technical depth and judgment to know the difference. What You'll Do * Build and deploy production-grade AI ...

Socket.dev

WI · On-site

$115 - $160/hr

... customers in optimizing AI-driven threat detection models and automated response workflows ... Configure and tune machine learning algorithms to reduce false positives while maintaining high ...

Urus Group LP

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

Model selection and evaluation, knowing when linear regression, optimization, or a lookup table ... Cloud AI infrastructure fluency, specifically Databricks and AWS. * Experiment design and ...

Briggs & Stratton

AI Solutions Lead

Wauwatosa, WI · Hybrid

Design and engineer Agentic AI integrations that sit on top of legacy architecture, specifically optimizing and automating workflows within manufacturing execution and ERP ecosystems like SAP across ...

Briggs & Stratton

AI Solutions Lead

Wauwatosa, WI · Hybrid

Design and engineer Agentic AI integrations that sit on top of legacy architecture, specifically optimizing and automating workflows within manufacturing execution and ERP ecosystems like SAP across ...

Briggs & Stratton

AI Solutions Lead

Wauwatosa, WI · On-site

Design and engineer Agentic AI integrations that sit on top of legacy architecture, specifically optimizing and automating workflows within manufacturing execution and ERP ecosystems like SAP across ...

Briggs & Stratton

AI Solutions Lead

Wauwatosa, WI · On-site

Design and engineer Agentic AI integrations that sit on top of legacy architecture, specifically optimizing and automating workflows within manufacturing execution and ERP ecosystems like SAP across ...

Qualysoft

$52.75 - $72.75/hr

Design, development and optimization of complete Retrieval-Augmented Generation pipelines ... Integration of AI applications into existing IT, data, database and cloud landscapes * Design and ...

Deloitte

Google AI Architect

Milwaukee, WI

Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization ...

McFadyen Digital

WI · On-site

$130 - $190/hr

Optimize and report on our AEO/GEO/SEO to improve our domain authority on AI for ecommerce, marketplace, and related topics. * Lead, mentor, and drive the performance of a handful of direct report ...

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Ai Optimization information

What are common challenges faced by professionals in AI optimization roles, and how can they be overcome?

Professionals in AI Optimization often encounter challenges such as balancing model accuracy with computational efficiency, handling large and complex datasets, and staying updated with rapidly evolving algorithms. To overcome these, it's important to collaborate closely with data engineers and domain experts, utilize scalable computing resources, and continuously invest in learning new optimization techniques. Participating in knowledge-sharing forums and leveraging open-source tools can also help address these challenges effectively.

What are the key skills and qualifications needed to thrive as an AI optimization specialist, and why are they important?

To thrive as an AI Optimization Specialist, you need a strong background in computer science, mathematics, and machine learning, often supported by a degree in a related field. Proficiency with programming languages like Python, optimization frameworks (such as TensorFlow or PyTorch), and knowledge of cloud platforms are typically required, along with relevant certifications. Analytical thinking, problem-solving, and effective communication are essential soft skills for translating complex data into actionable solutions. These skills ensure the development of efficient, scalable AI models that drive business value and innovation.

What is the difference between Ai Optimization vs Data Scientist?

AspectAi OptimizationData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Computer Science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentTech companies, AI-focused teams, R&D departmentsResearch institutions, tech firms, finance, healthcare
Employer & Industry UsagePrimarily in AI development, machine learning optimization projectsData analysis, predictive modeling, data-driven decision making

Ai Optimization specialists focus on enhancing AI models' performance and efficiency, often working on machine learning algorithms and deployment. Data Scientists analyze large datasets to extract insights, build predictive models, and support decision-making. While both roles require strong technical skills and knowledge of data and algorithms, Ai Optimization is more specialized in refining AI systems, whereas Data Scientists have a broader scope in data analysis and interpretation.

What is AI optimization?

AI optimization involves developing and applying algorithms to improve the performance, efficiency, or accuracy of artificial intelligence systems. AI optimization specialists often work with machine learning models, tuning parameters, and using tools like Python or TensorFlow to enhance AI capabilities. Strong analytical skills and knowledge of optimization techniques are essential for this role.

Which AI Optimization job is highly paid?

Senior AI Optimization engineers and machine learning engineers specializing in AI model efficiency and deployment tend to have the highest salaries in the field. These roles often require advanced skills in deep learning, programming, and data analysis, and they typically command higher compensation due to their technical complexity and impact on business performance.

What are popular job titles related to Ai Optimization jobs in Wisconsin?

For Ai Optimization jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Ai Optimization jobs in Wisconsin look for?

The top searched job categories for Ai Optimization jobs in Wisconsin are:

What cities in Wisconsin are hiring for Ai Optimization jobs?

Cities in Wisconsin with the most Ai Optimization job openings:

Ai Optimization jobs near you
Infographic showing various Ai Optimization job openings in Wisconsin as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Whitewater, WI • On-site

Other

Re-posted 27 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply