Senior Computer Vision/AI Engineer

Responsibilities

• Lead the full lifecycle of Computer Vision and ML model development — from data collection and labeling through deployment and monitoring in production environments.
• Research and implement deep learning models for computer vision tasks including detection, segmentation, classification, tracking, and real-time inference.
• Drive CV projects from prototyping to production, in alignment with product and platform goals.
• Collaborate with product, hardware, and cloud teams to design end-to-end intelligent features across the stack.
• Arcitect technically robust, scalable, and reliable AI systems in collaboration with cross-functional teams.
• Solve complex physical-world challenges through structured experimentation and performance optimization.
• Prioritize and manage multiple initiatives to ensure model performance, reliability, and compliance.
• Stay at the forefront of ML/AI and foundational models, integrate key innovations into the product roadmap.
• Evaluate emerging AI/ML trends and apply them to enable transformative infrastructure automation solutions.

Requirements

• 7+ years of experience in computer vision and ML, with deep expertise in applied deep learning.
• Proven ability to deliver production-grade AI/ML solutions in fast-paced, real-world environments.
• Full-stack ML development lifecycle experience: data labeling and curation, model training, evaluation, optimization, and deployment.
• Hands-on technical skills with DL frameworks (PyTorch or TensorFlow) and string programming skills in Python (C++ is a plus).
• Hands-on experience with CNNs, YOLO, Vision Transformers, model compression, and real-time inference optimization.
• Hands-on experience deploying models in cloud platforms (AWS/GCP/Azure) and edge devices using TensorRT, ONNX, or TFLite.
• Strong problem solving and analytical skills, with the ability to convert ambiguity into actionable insights.
• Excellent team work and collaboration skills; ability to work cross-functionally with software, hardware, and product teams.
• Effective communicator, capable of conveying complex technical concepts to both technical and non-technical stakeholders.
• Self-motivated, proactive, and thrives in a dynamic, fast-paced environment.

Qualifications

• PhD in Electrical Eng., Computer Science, or a related field with a focus on ML/AI for Computer Vision.
• Demonstrated research experience in CV with a strong record of publications and/or patents.
• Experience applying vision-based AI to real-time IoT systems or edge intelligence platforms.

Skills

• Deep expertise in applied deep learning.
• Proven ability to deliver production-grade AI/ML solutions in fast-paced, real-world environments.
• Full-stack ML development lifecycle experience.
• Hands-on technical skills with DL frameworks (PyTorch or TensorFlow).
• Hands-on experience with CNNs, YOLO, Vision Transformers, model compression, and real-time inference optimization.
• Hands-on experience deploying models in cloud platforms (AWS/GCP/Azure) and edge devices.
• Strong problem solving and analytical skills.
• Excellent team work and collaboration skills.
• Effective communication skills.
• Self-motivation and adaptability.

Bonus Qualifications

• Applied experience in CV for surveillance, physical-world perception problems, remote sensing, or structural health monitoring.
• Proficiency in Linux/Ubuntu environments; scripting and tooling around data and deployment workflows.
• Familiarity with Agile development practices and tools such JIRA, Git, Confluence.
• Experience with embedded systems, Docker containers, or Linux-based deployment pipelines.
• Prior experience in startup or high-growth environments building zero-to-one AI solutions.