Machine Learning Engineer

HCL Technologies Limited; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

HCL Technologies Limited in Singapore seeks an experienced ML Engineer to design, build, and maintain scalable AI solutions within a DevOps environment, collaborating with cross-functional teams. You will work on LLMs, multi-agent systems, and RAG-grounded AI, focusing on reliability, performance, and integration with enterprise data.

Python expertise and ML frameworks are essential. This role requires 6–8 years of hands-on ML experience, strong problem-solving, and a track record of delivering

Qualifications

• Bachelor’s degree in data science, CS, mathematics, statistics, or related field.
• Strong Python programming with ML libraries (TensorFlow or PyTorch).
• 6-8 years of relevant ML/data science experience.
• Proven experience with Large Language Models (LLMs).

Responsibilities

• Develop, deploy, and optimize ML/AI solutions for complex business challenges.
• Create multi-agent systems and enable AI models with function/tool-calling.
• Design RAG systems to ground AI in enterprise data.
• Assess and integrate AI models for performance and reliability.
• Optimize AI workflows and agents for production use cases.
• Test and refine prompts and few-shot examples for accuracy and safety.
• Collaborate with platform teams and data scientists to integrate solutions.
• Participate in code reviews, testing, and debugging.

Skills

Python programming

TensorFlow

PyTorch

LLMs expertise

AI agents workflows

Data preprocessing

Feature engineering

Statistics & math

DevOps & tooling

Debugging skills

Education

Bachelor’s degree in data science

Bachelor’s in Computer Science

Bachelor’s in Mathematics/Statistics

Job description

We are seeking a skilled machine Learning engineer (ML Eng) 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
• 6-8 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.