Relevant certifications such as AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate. Work Experience
Relevant certifications such as AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate. Work Experience
Master's or PhD in Computer Vision, Machine Learning, Robotics, or a related discipline ... quantization, pruning, or distillation. * Experience with industrial or safety-relevant vision ...
Master's or PhD in Computer Vision, Machine Learning, Robotics, or a related discipline ... quantization, pruning, or distillation. * Experience with industrial or safety-relevant vision ...
Senior AI Engineer - SFL Scientific
Milwaukee, WI · On-site
$103K - $141K/yr
Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...
Senior AI Engineer - SFL Scientific
Milwaukee, WI · On-site
$103K - $141K/yr
Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...
Senior AI Engineer / AI Solutions Architect
Brookfield, WI · On-site
$51.75 - $66.75/hr
This role sits at the intersection of software engineering, machine learning, enterprise architecture, data platforms, and AI product development. We are not looking for someone who simply deploys ...
Senior AI Engineer / AI Solutions Architect
Brookfield, WI · On-site
$51.75 - $66.75/hr
This role sits at the intersection of software engineering, machine learning, enterprise architecture, data platforms, and AI product development. We are not looking for someone who simply deploys ...
Senior AI Engineer / AI Solutions Architect
$51.75 - $66.75/hr
This role sits at the intersection of software engineering, machine learning, enterprise architecture, data platforms, and AI product development. We are not looking for someone who simply deploys ...
Senior AI Engineer / AI Solutions Architect
$51.75 - $66.75/hr
This role sits at the intersection of software engineering, machine learning, enterprise architecture, data platforms, and AI product development. We are not looking for someone who simply deploys ...
GenAI Python Systems Engineer - Experienced Associate
Milwaukee, WI · On-site
$63K - $140K/yr
Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale, enabling informed ...
GenAI Python Systems Engineer - Experienced Associate
Milwaukee, WI · On-site
$63K - $140K/yr
Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale, enabling informed ...
AI Solutions Engineering Delivery Lead
Milwaukee, WI · On-site
$101K - $133K/yr
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...
AI Solutions Engineering Delivery Lead
Milwaukee, WI · On-site
$101K - $133K/yr
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...
Senior Engineer- System Integration
Milwaukee, WI · On-site
$103K - $140K/yr
The Senior Engineer will define the scope and tasks for the investigations and may perform the ... Experience with statistics, econometrics, machine learning, or other mathematical modeling and ...
Senior Engineer- System Integration
Milwaukee, WI · On-site
$103K - $140K/yr
The Senior Engineer will define the scope and tasks for the investigations and may perform the ... Experience with statistics, econometrics, machine learning, or other mathematical modeling and ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Deploy and manage machine learning models across cloud and on-premise environments. * Implement ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
Machine Learning Engineer Quantization information
See Milwaukee, WI salary details
$31K - $45.5K
1% of jobs
$45.5K - $60.1K
1% of jobs
$60.1K - $74.6K
5% of jobs
$74.6K - $89.1K
6% of jobs
$101.1K is the 25th percentile. Wages below this are outliers.
$89.1K - $103.6K
14% of jobs
$103.6K - $118.1K
14% of jobs
The median wage is $125.3K / yr.
$118.1K - $132.6K
18% of jobs
$132.6K - $147.1K
14% of jobs
$150.1K is the 75th percentile. Wages above this are outliers.
$147.1K - $161.6K
12% of jobs
$161.6K - $176.1K
11% of jobs
$176.1K - $190.6K
5% of jobs
$31K
$126.9K
$190.6K
How much do machine learning engineer quantization jobs pay per year?
What does a machine learning engineer quantization do?
What are some common challenges machine learning engineers face when implementing quantization techniques in production models?
What are the key skills and qualifications needed to thrive as a machine learning engineer quantization, and why are they important?
What is the difference between Machine Learning Engineer Quantization vs Data Scientist?
| Aspect | Machine Learning Engineer Quantization | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or master's in CS, ML, or related; certifications in ML or AI | Bachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics |
| Work Environment | Developing optimized ML models, deploying quantized models for efficiency | Analyzing data, building predictive models, interpreting results |
| Industry Usage | Tech companies, AI hardware firms, embedded systems | Finance, healthcare, marketing, research institutions |
Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.
What are popular job titles related to Machine Learning Engineer Quantization jobs in Milwaukee, WI?
For Machine Learning Engineer Quantization jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Milwaukee, WI look for?
The top searched job categories for Machine Learning Engineer Quantization jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Machine Learning Engineer Quantization jobs?
Cities near Milwaukee, WI with the most Machine Learning Engineer Quantization job openings:
Principal Data & AI Architect
Waukesha, WI • On-site
Full-time
Posted 22 days ago
Key responsibilities
Design, develop, and implement Data & AI architectures, including enterprise data solutions, machine learning models, and generative AI systems.
Define technical strategies and roadmaps for Data & AI projects, ensuring alignment with business objectives.
Collaborate with data scientists, data engineers, and product teams to integrate Data & AI solutions into production environments.
Generac Power Systems rating
7.0
Based on 66 frontline employees who took The Breakroom Quiz
358th of 499 rated machine equipment manufacturers
Job description
For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future.
Ready to Power a Smarter World with us?
The Principal Data & AI Architect will be responsible for designing, developing, and implementing advanced Data & AI solutions and architectures that align with the company's strategic goals and objectives.
This role requires deep technical expertise, leadership, and the ability to collaborate across cross-functional teams to deliver scalable and innovative AI solutions.
Major Responsibilities :
Lead the design and development of Data & AI architectures, including designing and architecting Enterprise data/MDM solutions, machine learning models, deep learning frameworks, and generative AI systems. Responsible for analyzing, implementing and deploying these solutions both on-premises and in the cloud.
Define technical strategies and roadmaps for Data & AI-driven projects, ensuring alignment with business objectives.
Collaborate with data scientists, data engineers, business functional and product teams to integrate Data & AI solutions into production environments.
Advice, oversee the evaluation and adoption of Data & AI technologies, tools, and platforms.
Serve as the technical leader and mentor to Data & AI and engineering teams.
Deliver scalable, secure, and optimized Data & AI solutions.
Lead Data & analytic literacy of the organization and serve as a translator of deep technical concepts into simple business vernacular.
Be aware and lead industry trends and advancements in Data & AI to help maintain a competitive edge.
Communicate complex technical concepts to non-technical stakeholders effectively.
This is an individual contributor role.
Minimum Job Requirements:
Education
Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field also acceptable.
Work Experience
8 or more years of experience in AI, machine learning, or data science, with at least 4 years in a senior or lead architect role.
Proven track record of designing and deploying large-scale Data & AI systems in production environments.
Experience leading cross-functional teams in the delivery of complex AI projects.
Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Knowledge / Skills / Abilities
Must be deeply curious, desire to experiment.
Expertise in machine learning algorithms, Neural networks, Genetic Algorithms, Decision trees, Business dynamic models, Agent based models, Advanced statistical techniques and operations research.
Strong proficiency in programming languages such as Python, R, or Java.
Ability to design scalable, secure, and efficient AI architectures.
Exceptional problem-solving and analytical skills.
Strong leadership and mentorship abilities, with a focus on fostering innovation and collaboration.
Excellent communication skills, capable of translating technical concepts to diverse audiences.
Ability to work in a fast-paced, dynamic environment and manage multiple priorities.
Preferred Job Requirements:
Education
Ph.D. In Operations Research, Data Science, or a closely related field.
Master's degree in a relevant field with significant research or project work in AI or machine learning.
Certification / License
Relevant certifications such as AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate.
Work Experience
Experience with generative AI and reinforcement learning.
Knowledge / Skills / Abilities
Publications or patents in AI, machine learning, or related fields.
Familiarity with DevOps practices and MLOps pipelines for AI deployment.
Experience in industries such as healthcare, finance, or technology.
Physical Requirements and Working Conditions
While performing the duties of this job, the employee is regularly required to talk and hear; and use hands to manipulate objects or controls. The employee is regularly required to stand and walk. On occasion, the incumbent may be required to stoop, bend, or reach above the shoulders. The employee must occasionally lift up to 25 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision, and the ability to adjust focus. Occasional travel.
"We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law."
What Generac Power Systems employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Generac
Sourced by ZipRecruiter
Industry
Electrical equipment, appliance, and component manufacturing and engine, turbine, and power transmission equipment manufacturing
Company size
1 - 10 Employees
Headquarters location
Eagle, WI, US