IC Resources
This range is provided by IC Resources. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$140,000.00/yr - $160,000.00/yr
Direct message the job poster from IC Resources
Ann Arbor, Michigan (Onsite preferred, hybrid considered)
US Citizens only
We’re supporting an international technology company developing cutting edge sensing and analytics systems used for real-time monitoring of large scale environments. Their U.S. team is expanding and building out a new capability that applies machine learning to complex time-series and spatial data, enabling automated detection and classification of events in challenging, noisy conditions.
This is a unique opportunity to apply your ML expertise to rich, multi-dimensional sensor data and see your work deployed in the field, from model design to edge deployment and continuous performance improvement.
The Role
You’ll join a collaborative group of scientists and engineers working at the intersection of data, signal processing, and machine learning. The work blends hands-on model development with practical system integration, solving problems that span from model training to real-world deployment.
What You’ll Do
Design, train, and evaluate ML models for pattern recognition, detection, and classification on large-scale sensor data
Experiment with CNNs, transformers, and other architectures suited for temporal and spectral data
Optimize models for efficient, low-latency performance on edge or embedded systems
Build and maintain workflows for data preparation, labeling, and model evaluation
Collaborate closely with data and signal processing engineers to improve accuracy and reduce false alarms
Contribute to automation of experiment tracking, model packaging, deployment, and monitoring
What You’ll Bring
3+ years of experience developing and deploying ML models in real-world applications
Strong Python skills and familiarity with frameworks such as PyTorch or TensorFlow
Understanding of core ML methods for time-series, image, or audio data
Practical experience with model optimization (quantization, pruning, TensorRT, etc.)
Working knowledge of MLOps concepts: experiment tracking, CI/CD, version control, automated testing
Strong analytical thinking, curiosity, and comfort working with noisy or incomplete datasets
Nice to Have
Background in physics, acoustics, or signal processing
Experience with embedded or edge computing environments
Familiarity with GitLab, Docker, Kubernetes, or ONNX model packaging
Why Join This team is applying advanced ML to a real world sensing platform that directly impacts operational performance. You’ll have a chance to innovate, deploy, and continuously refine models that move quickly from concept to live use.
U.S. citizenship and the ability to pass a background check are required due to the nature of the work.
Seniority level: Mid-Senior level
Employment type: Full‑time
Job function: Information Technology and Design
Industries: Engineering Services, Computers and Electronics Manufacturing, Software Development
#J-18808-Ljbffr
Base pay range
$140,000.00/yr - $160,000.00/yr
Direct message the job poster from IC Resources
Ann Arbor, Michigan (Onsite preferred, hybrid considered)
US Citizens only
We’re supporting an international technology company developing cutting edge sensing and analytics systems used for real-time monitoring of large scale environments. Their U.S. team is expanding and building out a new capability that applies machine learning to complex time-series and spatial data, enabling automated detection and classification of events in challenging, noisy conditions.
This is a unique opportunity to apply your ML expertise to rich, multi-dimensional sensor data and see your work deployed in the field, from model design to edge deployment and continuous performance improvement.
The Role
You’ll join a collaborative group of scientists and engineers working at the intersection of data, signal processing, and machine learning. The work blends hands-on model development with practical system integration, solving problems that span from model training to real-world deployment.
What You’ll Do
Design, train, and evaluate ML models for pattern recognition, detection, and classification on large-scale sensor data
Experiment with CNNs, transformers, and other architectures suited for temporal and spectral data
Optimize models for efficient, low-latency performance on edge or embedded systems
Build and maintain workflows for data preparation, labeling, and model evaluation
Collaborate closely with data and signal processing engineers to improve accuracy and reduce false alarms
Contribute to automation of experiment tracking, model packaging, deployment, and monitoring
What You’ll Bring
3+ years of experience developing and deploying ML models in real-world applications
Strong Python skills and familiarity with frameworks such as PyTorch or TensorFlow
Understanding of core ML methods for time-series, image, or audio data
Practical experience with model optimization (quantization, pruning, TensorRT, etc.)
Working knowledge of MLOps concepts: experiment tracking, CI/CD, version control, automated testing
Strong analytical thinking, curiosity, and comfort working with noisy or incomplete datasets
Nice to Have
Background in physics, acoustics, or signal processing
Experience with embedded or edge computing environments
Familiarity with GitLab, Docker, Kubernetes, or ONNX model packaging
Why Join This team is applying advanced ML to a real world sensing platform that directly impacts operational performance. You’ll have a chance to innovate, deploy, and continuously refine models that move quickly from concept to live use.
U.S. citizenship and the ability to pass a background check are required due to the nature of the work.
Seniority level: Mid-Senior level
Employment type: Full‑time
Job function: Information Technology and Design
Industries: Engineering Services, Computers and Electronics Manufacturing, Software Development
#J-18808-Ljbffr