Lead the end-to-end engineering of computer vision systems, from prototyping to production deployment
Translate research prototypes into robust, production-ready systems
Collaborate with AI researchers to implement state-of-the-art vision algorithms (object detection, tracking, segmentation, OCR, 3D vision, etc.)
Architect scalable, low-latency pipelines for image processing in production
Optimize models for inference via quantization, pruning, knowledge distillation, TensorRT, OpenVINO, ONNX, etc.
Build and maintain data pipelines for large-scale image/video datasets (collection, preprocessing, augmentation, labeling)
Integrate vision models with cloud infrastructure (AWS, GCP, Azure) and deploy scalable inference APIs or streaming solutions
Implement model monitoring, drift detection, and automated retraining workflows in production
Drive best practices for model evaluation, benchmarking, explainability, and validation under real-world conditions
Mentor engineers and foster a collaborative, high-performance engineering culture
Stay up-to-date with advances in computer vision and AI, evaluating new tools and techniques for practical adoption

7+ years of experience in computer vision/AI engineering, with 2+ years in a technical leadership role
Proven track record of leading cross-functional AI/ML engineering projects to production
Strong programming skills in Python and experience with PyTorch, TensorFlow, or similar frameworks
Expertise in modern computer vision techniques (object detection, segmentation, classification, tracking, etc.)
Experience deploying CV models in real-time, batch, and streaming pipelines
Proven experience deploying AI/ML models in cloud environments (AWS, Azure, GCP)
Solid understanding of ML Ops, Docker, Kubernetes, REST APIs, and cloud infrastructure automation
Experience with model lifecycle management (MLflow, Kubeflow, SageMaker)
Understanding of vision model evaluation metrics (mAP, IoU, precision/recall, latency, FPS, throughput)
Excellent problem-solving, architecture design, and mentoring skills

Generous paid time off (PTO): 35 days PTO to enable work/life integration and promotes a culture of trust.
Health & Wellness: Eligibility for healthcare benefits begin day one, plus retirement savings plans.
Financial future: While retirement savings plans vary by country, we help you plan for your future.
Family-First Support: Navigate family challenges with our assistance, securing time for both your loved ones and self-care.
Hybrid work: Find your balance with two days working from home, three days in the office, plus the freedom to work anywhere for up to two weeks a year.
Time off to volunteer and give back to your community.
Career Growth: E-learning opportunities and workshops, and global mobility potential.
Commute benefits: up to \$100/month per employee for commuting expenses.
Philanthropy: Our company matches employee donations up to \$500 per year for causes close to your heart.

Lead AI / Computer Vision Engineer

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