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Remote Audio Signal Processing Jobs in Michigan (NOW HIRING)

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Perform advanced exploratory data analysis on large-scale sensory datasets (image, audio, radar ... remote servers and services, virtual computers and clusters. * Proficiency in signal processing ...

Signal Advisors

Accounting Associate

Detroit, MI · Remote

Signal Advisors is on a mission to solve the retirement crisis. 69% of Americans do not work with a ... Complete accounting close processes in a timely and accurate manner, ensuring appropriate financial ...

General Motors

Staff Sensor Systems Engineer

Warren, MI · On-site +1

$189.30K - $290.70K/yr

Hybrid/Remote: If the candidate is within 50 miles of a GM Technical center, they will need to ... Technical depth in signal processing, link analysis, or ML across at least one relevant sensing ...

2020 Companies

Learning Specialist

Detroit, MI · Remote

Work remote * Competitive salary of $55,000, paid weekly * Next day pay on-demand with DailyPay ... Strong skills in using technology-based tools and processes for creative design and training ...

2020 Companies, Inc.

Learning Specialist

Detroit, MI · Remote

Work remote * Competitive salary of $55,000, paid weekly * Next day pay on-demand with DailyPay ... Strong skills in using technology-based tools and processes for creative design and training ...

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Remote Audio Signal Processing information

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

To excel as a Remote Audio Signal Processing Engineer, you need strong knowledge of digital signal processing (DSP), audio algorithms, and programming skills, typically supported by a degree in electrical engineering, computer science, or a related field. Expertise in tools like MATLAB, Python, C++, and familiarity with platforms such as JUCE or VST, as well as experience with audio editing and analysis software, is highly valuable. Excellent problem-solving, communication, and self-motivation are essential soft skills for managing tasks independently and collaborating with distributed teams. These skills and qualifications are critical for developing high-quality audio solutions and ensuring effective project delivery in a remote work environment.

What are some common challenges faced by professionals in remote audio signal processing roles, and how can they be addressed?

Professionals in remote audio signal processing often encounter challenges such as latency issues, inconsistent audio quality due to varying internet connections, and difficulties in real-time collaboration with team members or clients. To address these, it’s important to use reliable communication platforms, leverage cloud-based audio tools that support version control, and establish clear file-sharing protocols. Regular virtual meetings and clear documentation can also help ensure smooth collaboration and consistent project outcomes.

What is remote audio signal processing?

Remote audio signal processing refers to the analysis, modification, and enhancement of audio signals using digital algorithms, typically performed from a location different from where the audio was recorded or is being used. Professionals in this field work with technologies such as noise reduction, echo cancellation, audio compression, and effects processing, often leveraging cloud-based tools and platforms. This allows for real-time audio improvements or transformations in applications like teleconferencing, streaming, and music production, all managed remotely.

What is the difference between Remote Audio Signal Processing vs Remote Audio Engineering?

AspectRemote Audio Signal ProcessingRemote Audio Engineering
CredentialsKnowledge of audio algorithms, signal processing certificationsAudio engineering certifications, experience with recording/mixing
Work EnvironmentPrimarily software-based, focused on digital signal manipulationStudio or live sound environments, often involving hardware setup
Industry UsageTech companies, software development, audio tech startupsMusic production, broadcasting, live events
Search & Comparison IntentFocus on technical signal processing skillsFocus on audio production and engineering expertise

Remote Audio Signal Processing involves developing and applying algorithms to manipulate audio signals digitally, often requiring programming and technical skills. Remote Audio Engineering focuses on capturing, mixing, and producing audio content, emphasizing hands-on technical and creative skills. While both roles work remotely and in the audio industry, their core responsibilities and skill sets differ significantly.

What are popular job titles related to Remote Audio Signal Processing jobs in Michigan? For Remote Audio Signal Processing jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Audio Signal Processing jobs in Michigan look for? The top searched job categories for Remote Audio Signal Processing jobs in Michigan are:
What cities in Michigan are hiring for Remote Audio Signal Processing jobs? Cities in Michigan with the most Remote Audio Signal Processing job openings:
Remote Audio Signal Processing jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Canopy

Detroit, MI • On-site, Remote

$126K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

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6.8

Company rating: 6.8 out of 10

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Job description

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat vehicle and content theft. In this senior role, you'll play a pivotal part in shaping our AI roadmap, mentoring junior engineers, and influencing system architecture decisions. This is a high-impact role with visibility across engineering and product leadership.
Responsibilities:
  • Contribute to the design, development, and deployment of robust machine learning models for production use in real-world security applications.
  • Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring.
  • Establish and refine best practices in our ML system architecture, CI/CD pipelines for ML, and reproducible research methodologies.
  • Collaborate with cross-functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery.
  • Perform advanced exploratory data analysis on large-scale sensory datasets (image, audio, radar, accelerometer) to derive insights and guide modeling strategies.
  • Stay ahead of industry advancements in machine learning, AI sensing, and signal processing, incorporating the latest innovations into Canopy's technology stack.
  • Mentor and guide junior engineers and contribute to the hiring process and technical reviews.

Requirements
  • 5+ years of professional experience developing and implementing ML for perception systems with expertise in at least one of either RADAR, camera, or LiDAR.
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
  • Expertise in Python with extensive experience in at least one deep learning framework (PyTorch or TensorFlow.
  • Proven ability to develop production-grade ML applications for training, evaluation and inference on large-scale datasets.
  • Experience creating C/C++ applications utilizing modern language features and build systems, preferably for porting ML inference applications from Python to edge devices/embedded systems.
  • White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural network models and architectures (CNNs, transformers) with significant experience applying them for perception systems.
  • Experience implementing and applying dynamic object tracking, with experience using sensor fusion as a preference.
  • Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and services, virtual computers and clusters.
  • Proficiency in signal processing techniques such as time/frequency-domain processing (e.g. Fourier Transform), filtering, and noise reduction.
Preferred Qualifications:
  • Experience in deploying models to edge hardware, including experience with PyTorch and ONNX and model compression techniques, e.g. quantisation and pruning.
  • Experience using cloud computing platforms, e.g., AWS or GCP.
  • Experience with MATLAB for algorithm prototyping and research.
  • Experience with Docker or containerisation.
  • Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.

Benefits
  • Comprehensive medical benefits coverage, dental plans and vision coverage.
  • Health care and dependent care spending accounts.
  • Employee and Family Assistance Program (EAP).
  • Employee discount programs.
  • Retirement plan with a generous company match.
  • Generous Paid Time Off, Sick, and Holidays
  • Family Leave (Maternity, Paternity)
  • Short- and long-term disability
  • Life insurance and accidental death & dismemberment insurance

Compensation Range
Compensation may vary depending on skills and experience.
Base Salary: $126,000 - $180,000
Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting-edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success.
Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

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