Machine Learning Engineer developing and implementing ML models for lending at Blue Whale Lending LLC. Collaborating with teams to enhance data insights and validate model performance.
About the role
- Applied ML Engineer contributing to machine learning and perception tasks for edge-intelligent maritime systems. Collaborating with cross-functional teams to deliver real-world AI solutions.
Responsibilities
- 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
- 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
- Flexible working hours with occasional deadlines requiring high availability.
- Opportunity to work on innovative projects with a global impact.
Job title
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