Machine Learning Engineer

HCL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

HCL SINGAPORE PTE. LTD. is seeking a skilled Machine Learning Engineer to join an agile ML & AI team in Singapore.

You will design, build, and maintain scalable AI solutions in a DevOps environment, contributing across the full lifecycle from concept to deployment and collaborating with cross-functional teams. The role requires 3–6 years of ML/data science experience, strong Python, and expertise with TensorFlow or PyTorch.

Qualifications

• Bachelor’s degree in data science, CS, mathematics, statistics or related field.
• Strong Python programming skills with ML libraries.
• 3–6 years of ML/data science experience and LLMS experience.

Responsibilities

• 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
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate ML solutions into existing systems
• Participate in code reviews, testing, and debugging to ensure quality and reliability of ML solutions
• Excellent communication and collaboration skills with cross-functional teams and stakeholders at all levels of the organization

Skills

Python programming

ML libraries

LLMs

AI agents

DevOps

Education

Bachelor’s degree in data science, CS, mathematics, statistics

Tools

TensorFlow

PyTorch

Job description

We are seeking a skilled Machine Learning engineer (ML Eng) to join one of our agile development teams in our ML & AI department. In this role, you will play a key part in designing, building, and maintaining robust, scalable AI solutions within a DevOps environment. You'll contribute across the entire lifecycle - from concept to deployment and collaborate closely with cross-functional teams to deliver high-quality digital solutions.

Responsibilities

• 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 prompts 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
• Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization
• Ability to manage personal workloads effectively, to prioritize tasks, manage timelines, and deliver high-quality results on schedule
• Continuous learning mindset, with a passion for staying up to date with the latest advancements in machine learning and artificial intelligence
• Attention to detail and commitment to producing high-quality, reliable, and maintainable code

Skills Requirement

• Bachelor’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
• 3 - 6 years of relevant work experience in machine learning, data science or a related field
• 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.