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Audio Machine Learning Jobs in Wisconsin (NOW HIRING)

Howard

Research Assistant

Downing, WI

$21 - $31/hr

... creating audio captcha technology. The candidate should be well-informed about the scientific ... in machine learning and data science; advanced degrees may offset experience requirements ...

Sadoff

2nd Shift Maintenance Laborer

Fond Du Lac, WI · On-site

Learning and Training: Actively participate in Safety Training Programs and on-the-job learning ... Must be able to traverse facilities and machinery by climbing, balancing, lifting, walking ...

NATIONAL YOUTH ADVOCATE PROGRAM

Assistant Educator

Madison, WI · On-site

$15.50 - $20.50/hr

Work with individual children in the classroom to promote their learning and development. MINIMUM ... Proficient use of desktop and laptop computers, smartphones and tablets, printers, fax machines ...

Monitise

Technical Relationship Manager

Milwaukee, WI

... learning or self-service capabilities * Experience training clients or internal associates on ... This role requires use of a computer and audio equipment. Travel: This role requires regular travel ...

All JobsAudio Machine Learning JobsAudio Machine Learning Jobs in Wisconsin

Audio Machine Learning information

What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?

To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.

Will MLE be replaced by AI?

In the context of an Audio Machine Learning (ML) role, AI tools and automation are increasingly used to assist with tasks like data processing and model deployment. However, MLE professionals are essential for designing, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Human expertise remains critical for interpreting results and ensuring system performance.

What are the typical daily responsibilities of someone working in Audio Machine Learning?

Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.

What is an Audio Machine Learning job?

An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.

Which 5 jobs will survive AI?

Audio Machine Learning specialists are likely to continue in demand as AI advances because their expertise in developing and refining audio recognition systems requires specialized skills that are difficult to automate fully. Roles involving creative audio design, audio engineering, and human oversight of AI systems are also expected to persist. These jobs often require a combination of technical knowledge, domain expertise, and critical thinking that AI cannot easily replace.

What engineer makes $500,000 a year?

Senior audio machine learning engineers with extensive experience, advanced skills in deep learning and signal processing, and often working at large tech companies or specialized research labs can earn salaries approaching or exceeding $500,000 annually. Compensation typically includes base salary, bonuses, and stock options, especially in high-demand industries like AI and audio processing.

Do audio engineers get paid well?

Audio engineers typically earn competitive salaries that vary based on experience, location, and industry sector. Entry-level positions may start lower, but experienced professionals working in recording studios, broadcasting, or live sound often have higher earnings, especially with specialized skills and certifications. Overall, the profession offers the potential for good compensation, particularly for those with technical expertise and a strong portfolio.
What are popular job titles related to Audio Machine Learning jobs in Wisconsin? For Audio Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning jobs in Wisconsin look for? The top searched job categories for Audio Machine Learning jobs in Wisconsin are:
Audio Machine Learning jobs near you
Machine Learning Engineer I

Machine Learning Engineer I

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
Milwaukee Tool is a company that values its people and culture as key to its success, focusing on innovative engineering solutions. As a Machine Learning Engineer, you will deploy machine learning models and collaborate with cross-functional teams to enhance power tool solutions, while ensuring project clarity and ownership.
Responsibilities:
• Deploy machine learning models in creative ways while working with highly cross-functional teams to make power tool solutions that change the lives of our users.
• Act as a technical expert in the creation and execution of these concepts into products, supporting the team through implementation, validation, and transfer to production.
• Leverage strong technical communication skills and fundamental project management abilities to ensure clarity and alignment across teams.
• Demonstrate a strong sense of ownership for projects and tasks, with a clear understanding of how they connect to broader initiatives.
Qualifications:
Required:
• Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
• Completed course work or specialization in Machine Learning and/or Data Science
• Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
• Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
• Proficient developing and debugging code in Python
• Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
• Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
• Solid mathematical foundation in statistics, linear algebra, calculus and optimization
• Ability to travel up to 10% of the time (domestic and international).
Preferred:
• Master’s degree or PhD in Machine Learning or related field
• At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field are preferred
• Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
• Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
• Experience working with modern software development tools and version control tools
Company:
Milwaukee Tool manufactures electric power tools and accessories. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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