AI Machine Learning Engineer - Predictive Maintenance focus Job Singapore,IT/Tech

Job Summary

Startup Inno is seeking a highly skilled and innovative AI Machine Learning Engineer with a strong focus on Predictive Maintenance to join our growing technology team. In this role, you will design, develop, and deploy intelligent machine learning models that analyze large-scale industrial data to predict equipment failures, optimize asset performance, and reduce operational downtime.

You will work at the intersection of data science, artificial intelligence, and industrial engineering, collaborating closely with product managers, data engineers, and domain experts to build cutting-edge predictive systems for real-world applications across manufacturing, energy, logistics, and smart infrastructure.

Key Responsibilities

Design, develop, and deploy machine learning models for predictive maintenance and anomaly detection.
Analyze time-series and sensor data from industrial equipment to identify failure patterns and performance issues.
Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, validation, and deployment.
Develop scalable solutions using cloud platforms and MLOps best practices.
Collaborate with cross-functional teams to integrate ML models into production systems.
Continuously monitor and improve model performance using real-world feedback.
Conduct research on advanced AI/ML techniques and apply them to predictive analytics use cases.
Document model design, experiments, and system architecture for internal and external stakeholders.

Required

Skills and Qualifications

Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
Strong proficiency in Python and experience with ML frameworks such as Tensor Flow, PyTorch, or Scikit-learn.
Solid understanding of supervised and unsupervised learning algorithms.
Experience working with time-series data and predictive modeling.
Knowledge of data processing tools such as Pandas, Num Py, and Spark.
Familiarity with cloud platforms (AWS, Azure, or GCP).
Understanding of REST APIs and model deployment techniques.
Strong problem-solving and analytical thinking skills.

Experience

3+ years of experience in machine learning, data science, or AI engineering roles.
Hands-on experience in building predictive or anomaly detection systems.
Experience working in industrial, manufacturing, IoT, or operations-related environments is a strong plus.
Prior experience with real-time data streams and sensor data is highly desirable.

Working Hours

Full-time position (40 hours per week).
Flexible working hours with remote or hybrid work options.
Must be available for collaboration across different time zones when required.

Knowledge, Skills, and Abilities

Deep understanding of machine learning lifecycle and model evaluation techniques.
Ability to translate business problems into data-driven solutions.
Strong communication skills to explain complex technical concepts to non-technical stakeholders.
Excellent teamwork and collaboration mindset.
High level of curiosity, adaptability, and continuous learning.
Ability to work independently in a fast-paced startup environment.

Benefits

Competitive salary and performance-based incentives.
Flexible remote working environment.
Opportunities for professional growth and career advancement.
Access to cutting-edge AI tools and technologies.
Learning and development budget for courses and certifications.
Inclusive, innovative, and collaborative company culture.
Health and wellness benefits (as per location).

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