Machine Learning Engineer

HCL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

HCL SINGAPORE PTE. LTD. is seeking a skilled Machine Learning Engineer to join an agile development team in the ML & AI field. You will design, build, and maintain robust, scalable AI solutions within a DevOps environment.

You will develop, deploy, and optimize ML/AI systems, create multi-agent setups with tool-calling, and Ground AI responses using enterprise data. Collaboration with data engineers, scientists, and platform teams is essential to deliver reliable ML deployments.

Qualifications

• Bachelor’s degree in data science, CS, math or related field.
• Strong Python and ML libraries/dl frameworks experience.
• 6-9 years of ML/data science experience.
• Proven experience with Large Language Models (LLMs).
• Understanding of AI agents, governance and orchestration.

Responsibilities

• Develop, deploy, and optimize ML/AI solutions for complex business challenges.
• Create multi-agent systems with function/tool-calling capabilities.
• Design RAG systems to ground AI in enterprise data.
• Assess and integrate AI models (LLMs) for reliability.
• Collaborate with platform teams and data scientists to integrate solutions.
• Participate in code reviews, testing, and debugging for ML solutions.
• Evaluate models using appropriate metrics and iterate improvements.
• Maintain high-quality, maintainable code and documentation.

Skills

Python programming

TensorFlow/PyTorch

LLMs experience

AI agents & orchestration

Data preprocessing

Statistics & math

DevOps practices

Problem solving

Effective communication

Education

Bachelor’s degree in data science, Computer Science, Mathematics, Statistics, or a related field

Tools

TensorFlow

PyTorch

LLM orchestration frameworks

Job description

We are seeking a skilled machine Learning engineer to join one of our agile development teams in our ML & AI field. In this role, you will play a key part in designing, building, and maintaining robust, scalable AI solutions within a DevOps environment.

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
• 6- 9 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.