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Posted 3 months ago
Requirements and responsibilities
About the Role
We are seeking a Senior AI/ML Engineer to lead the next wave of improvements in AI-powered vehicle damage detection and damage size assessment. Their current models have plateaued, and they need a fresh perspective to push accuracy, consistency, and real-world impact. This is a hands-on role with ownership of the full learning lifecycle, from data to deployment.
What You’ll Do
- Diagnose and resolve stagnation in existing ML and deep learning models.
- Boost the accuracy and consistency of vehicle damage detection and size estimation.
- Own the end-to-end model lifecycle: data collection, training, evaluation, deployment, and feedback loops.
- Analyze and improve dataset quality, labeling strategy, and balance.
- Redesign or refine model architectures, loss functions, and optimization strategies as needed.
- Align model objectives and evaluation metrics with business outcomes.
- Integrate production feedback to continuously improve model performance.
- Deploy, monitor, and iterate on models in AWS-based production environments.
- Collaborate closely with product, engineering, and AI teams.
What We’re Looking For
- 5+ years of hands-on experience in machine learning and deep learning.
- Proven experience improving underperforming or stalled ML models.
- Strong understanding of training dynamics, generalization, overfitting, and bias.
- Production experience with computer vision systems.
- Expertise in Python with PyTorch and/or TensorFlow.
- Experience working with large, imperfect, real-world datasets.
- Experience deploying and operating ML models in AWS.
Nice to Have
- Experience with defect detection, damage detection, or visual inspection.
- Familiarity with YOLO or similar architectures.
Why Join
- Take ownership of high-impact AI systems used in real-world vehicle assessments.
- Collaborate with a team passionate about delivering measurable business impact.
- Opportunity to bring fresh ideas and drive improvements across the AI lifecycle.
Optionally, you can add more information later (benefits, pre-screening questions, etc.)