ITCAN PTE. LIMITED
Machine Learning (ML) Engineer
Visa Source Listed
📍🇸🇬 Singapore📅3d ago
S$54,000—S$96,000/ year
≈ ₹34L — ₹60L per year
Software DebuggingTensorFlowMachine LearningCode ReviewBusiness OptimizationAI AgentsDevelopmentData SolutionsSystem TestingAI EvaluationAI ModelsCollaboration SolutionsPyTorchAI SafetyManufacturing Workflow Management
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Job Description
KEY FEATURES OF THE POSITION
Functional / Technical
• Develop, deploy, and optimize machine learning and AI solutions that address complex business challenges.
• Create multi-agent systems and equip AI models with function/tool-calling capabilities
• Design and implement RAG systems to ground AI responses in enterprise data
• Assess and integrate AI models (e.g. LLMs) ensuring optimal performance and reliability
• Optimize agentic workflows and AI agents for production use cases
• Testing and optimizing system prompt and few-shot example to ensure accurate, consistent, and safe AI outputs
• Performance evaluation of machine learning and AI models using appropriate metrics, evaluation sets and techniques, and continuously iterate and improve upon them
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions
Education and skills requirements
• Minimum 3 – 6 years of relevant work experience in machine learning, data science or a related field
• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
• Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks such as TensorFlow or PyTorch
• Proven experience working with Large Language Models (LLMs)
• Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns
• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
• Understanding software development best practices, including version control, testing, and documentation
• Excellent problem-solving and debugging skills, with the ability to identify and resolve issues quickly and effectively