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Applied ML Engineer
Quartermaster. Design, train, and evaluate models for tasks ranging from object detection and classification to anomaly detection and sensor-based inference.
Tech Stack
Tools & technologiesCloudPythonPyTorchRemote SensingTensorflow
About the role
Key responsibilities & impact- 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.
- Must be eligible to obtain/maintain a security clearance.
Requirements
What you’ll need- 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 production environments.
- 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
Comp & perks- Flexible working hours with occasional deadlines requiring high availability.
- Opportunity to work on innovative projects with a global impact.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningobject detectionclassificationanomaly detectionsensor-based inferencemodel optimizationdata augmentationsynthetic data generationPythondeep learning frameworks
Soft Skills
debuggingexperimentationproblem-solvingcollaborationcommunication
Certifications
Master’s degreePhD