Applied ML Engineer
Quartermaster AI
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
CloudPythonPyTorchRemote SensingTensorflow
About the role
- Design, train, and evaluate models for tasks ranging from object detection and classification to anomaly detection and sensor-based inference
- Optimize model architectures and inference pipelines for performance on embedded/edge hardware under compute and bandwidth constraints
- Contribute to dataset development and labeling strategy, including data augmentation, synthetic data generation, and domain adaptation
- Support prototyping and experimentation across a variety of AI subfields, including computer vision, signal processing, and multi-modal fusion
- Implement real-time pipelines for processing sensor data on-device and in cloud environments
- Develop tools and scripts for benchmarking, data visualization, and debugging ML model performance
- Stay current with the latest research and tools in machine learning and evaluate their applicability to our product roadmap
- Participate in code reviews, team knowledge sharing, and internal technical documentation
Requirements
- Master’s or PhD in Computer Vision, Machine Learning, Robotics, or related field. Bachelors candidates considered on a case by case basis.
- 4+ years of experience building and deploying machine learning models in
- Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow
- Comfortable working with a range of data types (images, time-series, geospatial, RF, etc.)
- Experience with edge or embedded ML deployments, including model compression and hardware-aware optimization
- Familiarity with common ML practices including cross-validation, hyperparameter tuning, and model monitoring
- Excellent debugging, experimentation, and problem-solving skills
- Strong collaboration and communication skills with both technical and non-technical team members
- Bonus: experience in maritime, aerospace, or other remote sensing domains
Benefits
- Competitive salary
- Flexible work hours and the option for remote work.
- Opportunities for professional development and continued education.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningobject detectionclassificationanomaly detectionsensor-based inferencemodel optimizationdata augmentationsynthetic data generationPythondeep learning frameworks
Soft skills
debuggingexperimentationproblem-solvingcollaborationcommunication
Certifications
Master’s degreePhD