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Remote Machine Learning Researcher Jobs in Michigan

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

... reproducible research methodologies. * Collaborate with cross-functional stakeholders including ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222K - $227K/yr

Research, design, and develop new machine learning solutions and algorithms for driverless technology company. Explore, prototype, validate, and iterate new algorithms and strategies. Drive efforts ...

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and ...

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Remote Machine Learning Researcher information

What are Remote Machine Learning Researchers?

Remote Machine Learning Researchers are professionals who study, design, and develop machine learning algorithms and models while working outside of a traditional office environment. They typically analyze data, conduct experiments, and collaborate with teams or organizations virtually to advance artificial intelligence technologies. Their work may involve tasks such as building predictive models, publishing research papers, or contributing to open-source machine learning projects. Being remote allows them flexibility in location and often the ability to work with international teams. Strong programming, mathematical, and communication skills are essential in this role.

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

To thrive as a Remote Machine Learning Researcher, you need a strong background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Familiarity with machine learning frameworks (TensorFlow, PyTorch), cloud computing platforms, and version control systems (Git) is typically required, along with published research or contributions to academic conferences. Outstanding problem-solving ability, self-motivation, and excellent written communication are crucial soft skills for remote collaboration and knowledge sharing. These skills are essential for developing innovative models, contributing to cutting-edge research, and effectively collaborating in a distributed team environment.

What are the common challenges faced by remote machine learning researchers when collaborating with global teams?

Remote machine learning researchers often collaborate with team members across different time zones and cultural backgrounds, which can make synchronous meetings and real-time problem-solving challenging. Communication of complex ideas, such as model architectures or experimental results, may require extra effort through detailed documentation and regular virtual check-ins. However, most organizations use collaborative tools like version control systems, project management platforms, and video conferencing to bridge these gaps, ensuring that research progress stays on track and team members remain aligned.
What are the most commonly searched types of Machine Learning Researcher jobs in Michigan? The most popular types of Machine Learning Researcher jobs in Michigan are:
What cities in Michigan are hiring for Remote Machine Learning Researcher jobs? Cities in Michigan with the most Remote Machine Learning Researcher job openings:
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 23 days ago


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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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