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Audio Machine Learning Intern Jobs in Ohio (NOW HIRING)

Miamioh

Goggin Intern for Programming

Oxford, OH

$14.25 - $19/hr

... management machines, as assigned * Assist with the marketing efforts for all Goggin programming ... We defend the freedom of inquiry that is the heart of learning and combine that freedom with the ...

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Audio Machine Learning Intern information

What does an Audio Machine Learning Intern do?

An Audio Machine Learning Intern assists in developing and improving machine learning models that process and analyze audio data. Their tasks may include data preprocessing, feature extraction, model training, and evaluation for applications like speech recognition, sound classification, or music analysis. Interns often collaborate with engineers and researchers to experiment with new algorithms and optimize audio-based AI systems. This role provides hands-on experience in both audio signal processing and machine learning techniques.

What types of projects can an Audio Machine Learning Intern expect to work on during their internship?

As an Audio Machine Learning Intern, you can expect to be involved in projects such as developing and fine-tuning audio classification models, working on speech recognition algorithms, or improving the accuracy of sound event detection systems. You may also assist with the collection and preprocessing of audio datasets, as well as support model evaluation and optimization. Collaboration with data scientists, audio engineers, and software developers is common, offering a hands-on learning environment and exposure to end-to-end machine learning workflows in the audio domain.

What are the key skills and qualifications needed to thrive as an Audio Machine Learning Intern, and why are they important?

To thrive as an Audio Machine Learning Intern, you need a solid background in signal processing, machine learning fundamentals, and programming skills, often supported by coursework or research in computer science or electrical engineering. Familiarity with Python, TensorFlow or PyTorch, and audio processing libraries like Librosa is typically required. Creativity, problem-solving abilities, and strong collaboration skills help you stand out in this role. These skills are crucial for developing innovative audio solutions, interpreting complex data, and working effectively within research or product teams.

What is the difference between Audio Machine Learning Intern vs Audio Data Analyst?

AspectAudio Machine Learning InternAudio Data Analyst
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fieldsDegree in Data Analysis, Statistics, or related fields; may have certifications in data tools
Work EnvironmentResearch labs, tech companies, or startups focusing on AI and audio techData-driven departments within media, entertainment, or tech companies
Employer & Industry UsageUsed in AI development, research projects, and product innovationUsed for analyzing audio data, improving user experience, and reporting

The Audio Machine Learning Intern focuses on developing models and algorithms for audio data, often in research or development settings. In contrast, the Audio Data Analyst primarily interprets audio data to generate insights and support decision-making. Both roles require familiarity with audio data, but the intern role emphasizes machine learning skills, while the analyst role centers on data analysis and reporting.

What are the most commonly searched types of Audio Machine Learning jobs in Ohio? The most popular types of Audio Machine Learning jobs in Ohio are:
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Audio Machine Learning Intern jobs near you

Vision Systems Engineer - Raymond, Ohio (on-site only)

Thomas & Reed, LLC

Dayton, OH • On-site

Contractor

Re-posted 25 days ago

Job description

Vision Systems Engineer
Location: ADC Raymond, OH
Contract to Hire
Duration: 12 month + conversion/extension

Description:

The HDMA Digital Innovation Division, Digital Manufacturing Unit, IoT Solutions Development group was created to survey Honda’s manufacturing business and develop strategy for prioritized development of digital solutions that enable improved production efficiency, quality, and safety for a sustainable future.
The IoT Solutions Engineer is engaging with NA regional plant floor customers to identify opportunities to develop and test technology/concepts and prove the ability to deliver reliable value to our customer. Ideal candidate for this role has a creator mindset, is excited to maintain awareness of digital technology developments, and then develop new, reliable solutions that enable Honda competitiveness, while also being risk averse.

• Development of new digital technology solutions such as vision inspection systems, AI and M/L analysis of machine/sensor data.
• Analyze user/customer needs along with manufacturing problems and align them with product/technology opportunities.
• Contribute to and execution of IoT strategy and roadmap for selected areas.
• Monitor developments of new technologies for IoT potential in future projects
• Support analytical processes, like machine learning in use within proof-of-technology concepts to deployed IoT projects.


QUALIFICATIONS, EXPERIENCE, & SKILLS

Minimum Educational Qualifications: Bachelor’s degree in engineering or engineering-related areas: electrical, controls, systems, computer science, data science or equivalent experience

Minimum Experience: 2+ years’ experience in manufacturing equipment controls, network design, embedded systems, machine learning and/or data engineering with a focus on the automotive industry

Other Job-Specific Skills:
-Understanding, extraction and interpretation of parameter data in a machine that represents the health of the machine components, proper operation, and effects on product quality.
-Knowledge of manufacturing equipment controls and logic – preferably in at least one of Mitsubishi, Rockwell, Siemens, or Omron PLCs.
-Understanding of computer vision algorithms such as segmentation, morphology, pose estimation, camera calibration, image enhancement, feature extraction, classification, 3D Vision and deep learning techniques.
-Experience implementing vision algorithms in C++, Python, HALCON, Matrox, Cognex, and/or Keyence, using traditional rules and/or deep learning.
-Experience with vibration, audio, or current signature analysis

Interested candidates please contact Sue HUettl at shuettl@trllc-cpa.com