AI / Machine Learning Engineer

Helius Technologies; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Helius Technologies is seeking an AI / Machine Learning Engineer to develop intelligent sensor- and edge-focused AI solutions. You will work on forecasting, anomaly detection, predictive diagnostics and energy optimisation across sensor, time-series, telemetry and image data.

Responsibilities include prototyping, experiments, and deploying models for cloud, edge, embedded or hybrid environments while collaborating with software, hardware, cloud and MLOps teams.

Qualifications

• At least 3 years of relevant experience in AI/ML engineering.
• Strong Python programming skills.
• Experience with PyTorch, TensorFlow, Scikit-learn.
• Experience with sensor, time-series, telemetry, image or operational data.
• Bachelor’s degree or higher in CS/AI/ML/Data Science/Engineering.

Responsibilities

• Develop and evaluate Machine Learning and Deep Learning models for forecasting, classification, anomaly detection, optimisation and predictive diagnostics.
• Analyse sensor, time-series, telemetry, image and operational data to identify patterns and develop AI-driven solutions.
• Build prototypes, conduct experiments, perform error analysis and compare different modelling approaches.
• Work with domain experts to define data requirements, features, labels, evaluation metrics and acceptance criteria.
• Optimise and package ML models for cloud, edge, embedded or hybrid deployment.
• Independently manage AI/ML 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.
• Apply modern AI-assisted development tools to support coding, testing, debugging and technical research.

Skills

Machine Learning

Deep Learning

Python

Education

Bachelor's degree or higher in CS/AI/ML/Data Science/Engineering

Tools

PyTorch

TensorFlow

Scikit-learn

Job description

AI / Machine Learning Engineer – Sensor & Edge AI

We are looking for an AI / Machine Learning Engineer to develop intelligent solutions using sensor, time-series, telemetry and operational data.

You will work on real-world AI applications involving areas such as sensor intelligence, anomaly detection, predictive diagnostics, energy optimisation and Edge AI, collaborating closely with software, hardware, embedded, cloud and product teams.

Key Responsibilities

• Develop and evaluate Machine Learning and Deep Learning models for forecasting, classification, anomaly detection, optimisation and predictive diagnostics.
• Analyse sensor, time-series, telemetry, image and operational data to identify patterns and develop AI-driven solutions.
• Build prototypes, conduct experiments, perform error analysis and compare different modelling approaches.
• Work with domain experts to define data requirements, features, labels, evaluation metrics and acceptance criteria.
• Optimise and package ML models for cloud, edge, embedded or hybrid deployment.
• Independently manage AI/ML 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.
• Apply modern AI-assisted development tools to support coding, testing, debugging and technical research.

Requirements

• Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering or a related discipline.
• At least 3 years of relevant experience in AI/ML Engineering, Machine Learning, Deep Learning, Data Science or Algorithm Development.
• Strong programming skills in Python.
• Hands‑on experience with PyTorch, TensorFlow, Scikit-learn or similar ML frameworks.
• Experience developing and evaluating ML/DL models using real-world datasets.
• Experience working with sensor, time-series, telemetry, image or operational data.
• Good understanding of model experimentation, evaluation, error analysis and performance optimisation.
• Ability to independently deliver end-to-end AI/ML projects.
• Familiarity with Git, APIs, automated testing, documentation and CI/CD.
• Strong communication skills and ability to work across engineering teams.