Working understanding of machine learning and deep learning fundamentals (supervised/unsupervised learning, neural networks, CNNs, RNNs/Transformers, model……
Experience with self-supervised learning, few-shot learning, or foundation models. Experience collaborating with engineers to productionize research outcomes.…
Experience building developer APIs or software frameworks used by other engineers. In the ML Engineering track, you will build the infrastructure that……
You’ll collaborate with international teams in a fast-moving environment that values ownership, proactive communication, and the ability to turn ideas into real……
Use your data analytics and data science expertise to derive valuable insights from datasets, build predictive models and machine-learning algorithms.…
Collaborate cross-functionally with software engineers, product managers, and analysts to integrate AI into products and workflows. NET, C++/C#, SQL and Cypher.…
Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, feature engineering and model……
Proficient in machine learning/deep learning frameworks, MLOps toolchains, and big data processing technologies; familiar with large model fine-tuning (LoRA,……
Apply Practical ML : Implement data analytics, forecasting models, and light machine learning where they materially elevate enterprise decision quality.…
Strong expertise on AI and machine learning technologies (e.g.: RAG pipelines, LoRA, Harness Engineering, etc). Experience with MLOps, LLMOps and AgentOps.…
Design and develop Smart Mobility & Smart City IoT software with integrated AI/ML capabilities, leveraging both custom models and pre-trained / open-source frameworks
Apply, fine-tune, and optimize machine learning and deep learning models for real-world IoT use cases — including forecasting, anomaly detection, and operational intelligence
Design, implement, integrate, and benchmark AI algorithms tailored to Smart Mobility scenarios, using established libraries and pre-trained models where appropriate
Build, deploy, and maintain end-to-end ML pipelines on Linux-based and cloud environments (AWS, Oracle Cloud, or equivalent), including data ingestion, training, inference, and monitoring stages
Document and maintain the functionality of software and AI model systems, including operational handover materials
Troubleshoot, debug, and upgrade existing software and AI/ML systems, including model retraining, performance tuning, and infrastructure optimization
Keep software and AI systems current with the latest features, frameworks, and techniques — supported by AI-assisted coding and modern developer tooling
Perform proof-of-concept (POC) work on the latest AI models, tools, and research ideas, with rapid prototyping using AI-assisted development
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Business Related with a strong technical track record, or equivalent practical experience
Strong Linux background — essential for ML infrastructure and deployment work
Cloud experience on AWS, Oracle Cloud, or equivalent platforms for hosting and operating AI/ML services
Hands-on experience with Python and common AI/ML libraries and frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, Hugging Face, OpenCV, or similar — including practical use of AI-assisted coding tools to accelerate development and debugging
Working understanding of machine learning and deep learning fundamentals (supervised/unsupervised learning, neural networks, CNNs, RNNs/Transformers, model evaluation metrics) — deep theoretical expertise not required if balanced by strong applied and deployment experience
Familiarity with data processing tools (e.g., NumPy, Pandas) and ability to work with large-scale, real-world datasets — including IoT telemetry, device fleet data, and sensor streams
Strong AI deployment, DevOps, and MLOps capability — including automation, scripting, monitoring, and multi-site failover (highly valued, given the IoT and city-scale nature of the role)
Comfortable working in an agile environment
Fluent in English with good written and oral communication; Cantonese and/or Mandarin a plus for regional collaboration
Job Type: Full-time Work Location: In person
Job Type: Full-time
Pay: $32,000.00 - $38,000.00 per month
Work Location: In person
Base pay range
The minimum salary is HK$32,000 and the max salary is HK$38,000.
HK$32,000 – HK$38,000/mo (Employer provided)
HK$35,000
/mo Median
Kowloon City
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