AI Engineer - Product Intelligence

Job Summary

The role will focus on areas such as sensor-based presence detection, energy optimization, anomaly detection, predictive diagnostics, intelligent control, and edge AI deployment. Potential projects may include mmWave radar-based presence detection, HVAC and thermostat energy-saving algorithms, Home Energy Management Systems, and device intelligence.

The successful candidate should have strong hands-on AI/ML development skills and the ability to independently own and deliver projects while working closely with product, hardware, embedded, cloud, and domain engineering teams.

Responsibilities

• Develop and evaluate ML/DL models for sensor intelligence, forecasting, classification, anomaly detection, optimization, and predictive diagnostics.

• Analyze sensor, time-series, telemetry, image, and operational data.

• Work with domain experts to define data requirements, features, labels, evaluation metrics, and acceptance criteria.

• Build prototypes, conduct experiments, compare technical approaches, and perform error analysis.

• Optimize and package validated models for cloud, edge, embedded, or hybrid deployment.

• Independently lead assigned AI projects from problem definition and technical design through development, testing, integration, and deployment.

• Collaborate with software, hardware, embedded, cloud, data, and MLOps teams to deliver production-ready AI solutions.

• Use AI-assisted coding tools to improve development, testing, debugging, documentation, and technical research.

Required Qualifications

• Bachelor’s degree or above in Computer Science, AI, Machine Learning, Data Science, Engineering, or a related field.

• At least 3 years of relevant experience in AI engineering, machine learning, deep learning, data science, or algorithm development.

• Strong Python programming skills.

• Hands-on experience with PyTorch, TensorFlow, scikit-learn, or similar frameworks.

• Solid understanding of model development, evaluation, experimentation, error analysis, and performance improvement.

• Experience working with real-world sensor, time-series, telemetry, image, or operational data.

• Ability to independently plan, execute, and deliver end-to-end AI or machine learning projects.

• Familiarity with Git, automated testing, APIs, documentation, and CI/CD.

• Good communication skills and ability to work with cross-functional engineering teams.

Preferred Qualifications

• Experience with mmWave radar, signal processing, sensor fusion, presence detection, or activity recognition.

• Experience with edge AI, ONNX, TensorRT, model compression, or embedded deployment.

• Experience with energy optimization, HVAC, HEMS, EV charging, predictive maintenance, or control algorithms.

• Familiarity with MLOps tools such as MLflow, Docker, Kubernetes, or model monitoring.

• Working knowledge of LLM applications, AI agents, tool calling, or agent workflows.

• Experience translating AI prototypes into reliable production solutions.

• Proficiency in C or C++ is an advantage.

• Professional proficiency in English; Mandarin or Cantonese is an advantage.