ML/AI Engineer

• Our client, a rapidly-growing AI technology company, is focusing on developing cutting-edge computer vision and edge AI solutions for various real-world environments across the globe.
• They have successfully implemented their solutions in Asia, Europe, and North America, with a dedicated team working towards overcoming operational challenges through practical AI solutions that combine machine learning, edge computing, and automation.
• This role presents an exciting opportunity to become a part of a highly skilled engineering team, contributing significantly to the transition of AI solutions from experimentation to large-scale deployment.
• The company is seeking an experienced ML Engineer with a strong background in computer vision to participate in the design, training, optimization, and deployment of AI models for real-world applications.
• In this role, collaboration with engineering and product teams will be crucial to enhance system decision-making, validate model performance, and ensure readiness for production in complex operational scenarios.

Responsibilities:

• Develop and enhance computer vision and deep learning models for practical applications.
• Focus on tasks related to object detection, tracking, and re-identification.
• Establish reliable evaluation, benchmarking, and validation procedures.
• Improve model performance for deployment in real-world environments.
• Engage with backend, platform, and product teams to integrate AI features into production systems.
• Analyze model performance, troubleshoot issues, and enhance system reliability.
• Contribute to tooling, experimentation pipelines, and technical decision-making processes.
• Support continuous improvement through data-driven experimentation and validation.

Requirements:

• Proficient in Python programming with a solid foundation in software engineering principles.
• Hands-on experience in deep learning and computer vision.
• Practical expertise in areas such as object detection, multi-object tracking, and re-identification.
• Thorough understanding of model evaluation methodologies and computer vision metrics.
• Experience in exporting and validating models using frameworks like ONNX.
• Ability to address model, data, or inference-related challenges efficiently.
• Capable of working on both ML research and engineering implementation.
• Proficiency in effectively utilizing AI-assisted development tools.
• Strong communication skills in English for collaboration with global teams.

Nice-to-haves:

• Familiarity with Vision-Language Models (VLMs).
• Experience with video-based or multi-camera AI systems.
• Knowledge of OpenVINO optimization and quantization (FP16 / INT8).
• Real-world deployment experience in industries like retail, manufacturing, or smart environments.
• Previous exposure to maintaining ML evaluation or benchmarking pipelines.