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Remote Audio Machine Learning Jobs in Michigan (NOW HIRING)

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Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

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Remote Audio Machine Learning information

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

How does a Remote Audio Machine Learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

What are the key skills and qualifications needed to thrive as a Remote Audio Machine Learning Engineer, and why are they important?

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

What is a Remote Audio Machine Learning job?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.
What are popular job titles related to Remote Audio Machine Learning jobs in Michigan? For Remote Audio Machine Learning jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Remote Audio Machine Learning jobs? Cities in Michigan with the most Remote Audio Machine Learning job openings:
Infographic showing various Remote Audio Machine Learning job openings in Michigan as of June 2026, with employment types broken down into 3% Internship, 73% Full Time, 3% Part Time, and 21% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution.
Data Scientist - Materials R&D - Remote-Travel

Data Scientist - Materials R&D - Remote-Travel

Intertape Polymer Group, Inc.

Marysville, MI • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Intertape Polymer Group rating

6.8

Company rating: 6.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

76th of 110 rated packaging manufacturers


Job description

Join the IPG Team!
Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions-we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!
This position can be based out of Marysville, MI, or work remotely with some travel as needed.
Title: Senior Data Scientist
Department: Research and Development
Immediate Supervisor: R&D Vice President
Status: Exempt Salaried
Position Purpose: The Senior Data Scientist willsupport R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.
Principle Accountabilities
  • Partner with polymer scientists, chemists, and engineers to support bio-polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structure-property-process relationships
  • Develop predictive models to support:
    • Material performance and property optimization
    • Formulation design and screening
    • Scale-up and process optimization
  • Design and analyze experiments (DOE) to maximize learning efficiency and reduce development timelines
  • Build and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis
  • Apply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasets
  • Collaborate with data engineering and IT teams to enable scalable data infrastructure for R&D
  • Communicate insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholders
  • Understanding of data visualization best practices
  • Experience working with batch or streaming data processes a plus
  • Contribute to data dictionaries and process flow diagrams for complex data solutions
  • Mentor junior data scientists or technical staff and contribute to data science best practices within R&D
  • Stay current with advances in materials informatics, polymer modeling, and applied AI in scientific research

Essential Skills and Experience
  • Bachelor's degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master's or PhD preferred
  • 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferred
  • Strong proficiency in Python and/or R for data analysis and modeling
  • Solid experience with SQL and working with structured and semi-structured datasets
  • Strong foundation in statistics, experimental design, and multivariate analysis
  • Demonstrated experience applying machine learning to real-world, noisy scientific or experimental data
  • Ability to work effectively in a cross-functional R&D environment
  • Strong communication skills with the ability to translate complex analyses into actionable insights
  • Familiarity with bio-polymers, sustainable materials, or polymer processing, preferred
  • Experience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferred
  • Experience deploying models to support R&D decision-making or manufacturing scale-up, preferred
  • Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferred
  • Prior experience mentoring or leading technical projects, preferred

Why Choose IPG?
At IPG, you will find more than just a job-you will find a place where your success is our success. We pride ourselves on a culture built around strong relationships, where every team member plays a crucial role in our growth. Whether it is through cross-department collaboration, continuous training, or sustainability-driven initiatives, we create an environment where you can thrive.
Our commitment to sustainability influences everything we do, from designing eco-friendly products to minimizing waste in our production processes. We are dedicated to building a greener future while providing safe, supportive workplaces for our people.
With over 40 years of industry expertise and a proven track record of growth and innovation, IPG offers a stable, secure environment where you can flourish!
We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities. Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed. Think big, dream bigger, and make an impact with IPG.
You belong here. Join us today!

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