Machine Learning Engineer – Computer Vision

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Take ownership of the modeling strategy for visual inspection, including the selection of architecture, training approaches, and targets for accuracy, latency, and false-reject rates.

• Establish and uphold the evaluation methodology and regression suite that governs model releases.

• Manage versioning, sampling, and auditing of labeled data.

• Enhance models for constrained edge environments through techniques such as quantization, runtime selection, and throughput optimization.

• Oversee drift detection, retraining triggers, and monitor production models across customer deployments.

• Collaborate with customers and application engineers on feasibility assessments, data collection strategies, and acceptance criteria.

• Set high standards for the ML discipline by providing design reviews, mentoring, and written guidance on architecture.

• Integrate agents and evaluations into the ML workflow, encompassing dataset triage, failure-mode analysis, and experiment scaffolding.

• Assess whether improvements in AI workflows result in enhanced cycle times.

• Report directly to the Director of Software Engineering.

⛳️ Requirements

• A Bachelor’s Degree or equivalent years of relevant experience in the field.

• Legal authorization to work in the United States is mandatory.

• This position will not sponsor individuals for employment visas, either currently or in the future.

• Typically requires over 8 years of relevant experience in a software product development setting.

• A Bachelor’s or advanced degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field.

• Proven experience in transitioning machine learning models from research to production deployment.

• Proficiency in deep learning for computer vision, covering areas such as detection, classification, segmentation, or anomaly detection.

• Experience in deploying vision models to edge or embedded platforms while adhering to fixed latency constraints.

• Strong expertise in either PyTorch or TensorFlow, along with knowledge in tools for dataset versioning, labeling quality, and experiment tracking.

• Familiarity with model optimization techniques, including quantization, pruning, distillation, TensorRT, or ONNX Runtime.

• Direct technical experience with customers: defining application scopes, establishing acceptance criteria, and articulating the limitations of models.

• Exposure to industrial or manufacturing settings, machine vision hardware, or PLC-based control systems.

• Experience in creating evaluation harnesses that enable teams to confidently implement model changes.

🏝️ Benefits

• Health Insurance that includes Medical, Dental, and Vision coverage.

• 401k plan.

• Paid Time Off.

• Parental and Caregiver Leave.

• Flexible Work Schedule, allowing you to coordinate with your manager for a schedule that accommodates your personal life.

• An annual target bonus of 8% of base salary.