Senior ML Engineer (Computer Vision & Video Analytics) at changiairport

, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

05 Jan, 26

Salary

0.0

Posted On

07 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Video Analytics, Deep Learning, Generative AI, Cloud Platforms, Python, C++, GPU Optimization, MLOps, Real-Time Data Streaming, Video Frameworks, CUDA, Docker, Kubernetes, AI Roadmap, Multimodal AI

Industry

Aviation and Aerospace Component Manufacturing

Description

We are seeking a Senior ML Engineer to lead the design and deployment of next-generation real-time computer vision and video analytics platforms. This role combines cutting-edge computer vision, Generative AI, and agentic AI to power large-scale, mission-critical solutions across edge, on-prem, and cloud environments. What You’ll Do Lead the architecture and development of enterprise-grade, real-time video analytics solutions. Build and optimize distributed data pipelines for high-volume, low-latency video streams. Integrate advanced deep learning and multimodal AI models (detection, segmentation, tracking, classification) into live video workflows. Apply Generative AI (LLMs, multimodal, RAG) to enhance situational awareness and adaptive system response. Drive GPU optimization and performance tuning for large-scale deployments. Shape our AI roadmap, evaluating and adopting the latest advancements in CV, GenAI, and agentic AI. Ensure scalability, reliability, and governance of deployed AI systems. What We’re Looking For Bachelor Degree with 6+ years of hands-on experience in computer vision, AI/ML, or video analytics, with real-world deployments. Strong expertise in cloud platforms (AWS, GCP) — experience with services like Sagemaker, Vertex AI, BigQuery, Kinesis, or equivalent. Proficiency with video frameworks (NVIDIA DeepStream, OpenCV, GStreamer) and modern CV models (YOLO, DETR, SAM, Transformers). Solid knowledge of real-time data streaming (Kafka, Pub/Sub, or similar). Strong programming skills in Python and C++, with experience in PyTorch, TensorFlow, TensorRT. Hands-on experience with GPU acceleration (CUDA), Docker/Kubernetes, and microservices for scalable AI systems. Familiarity with GenAI and agentic AI frameworks in production settings. Nice-to-Haves Experience with MLOps: model deployment, monitoring, lifecycle management. Understanding of video compression and streaming protocols (H.264, H.265, RTSP, WebRTC). Strong communication and leadership skills to influence both technical direction and business strategy.

Responsibilities

Lead the architecture and development of enterprise-grade, real-time video analytics solutions. Ensure scalability, reliability, and governance of deployed AI systems.