AI/ML Engineer (Permanent)

TALENTSIS PTE. LTD.; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

TALENTSIS PTE. LTD. is seeking a Senior AI/ML Architect to lead the design, development, and deployment of production-grade geospatial AI solutions in Singapore.

You will drive scalable architectures and collaborate with software engineers to integrate AI capabilities into end-to-end platforms. The role emphasizes ML operations, model performance, and reliability, with mentoring responsibilities and active engagement with product, business development, and sales teams to translate requirements

Qualifications

• Degree in Computer Science, Electrical Engineering, or a related discipline.
• 5+ years of experience in developing and deploying production-grade ML solutions.
• Strong foundation in ML and deep learning, including model development, evaluation, and optimisation.
• Proficient in Python with hands-on experience in PyTorch and scikit-learn, and OpenCV.
• Experience deploying and maintaining ML services, including API development and Docker.
• Experience with LLMs, RAG, retrieval optimisation, and graph databases is advantageous.
• Self-motivated with ownership, stakeholder management, and communication skills.
• Ability to mentor team members and collaborate across technical and business teams.

Responsibilities

• Provide technical leadership in the design, development, and deployment of production-grade AI/ML solutions for geospatial applications.
• Design and architect scalable ML systems, integrating AI into end-to-end platforms with software engineers.
• Drive model performance, reliability, and MLOps practices including deployment, monitoring, and optimisation.
• Collaborate with product, business development, and sales to translate requirements into technical delivery plans.
• Provide mentorship and guidance to engineers to support decision-making and capability development.
• Support pre-sales and post-sales activities with technical expertise.

Skills

Python

Machine learning

Deep learning

Mentoring

Stakeholder management

Communication

Education

Bachelor's degree in Computer Science or related

Tools

Docker

Flask/FastAPI/Node.js

OpenCV

Job description

Responsibilities:

• Provide technical leadership in the design, development, and deployment of production-grade AI and machine learning solutions, with a focus on geospatial applications.
• Design and architect scalable machine learning systems, working closely with software engineers to integrate AI capabilities into end-to-end platforms.
• Drive model performance, system reliability, and continuous improvement through MLOps best practices, including deployment, monitoring, and optimisation.
• Collaborate with product, business development, and sales teams to translate business requirements into clear technical solutions and delivery plans.
• Provide technical guidance and mentorship to engineers, supporting technical decision-making and capability development within the team.
• Support pre-sales and post-sales activities by providing technical expertise and consultation where required.

Requirements:

• Degree in Computer Science, Electrical Engineering, or a related discipline.
• At least 5 years of relevant experience in developing and deploying production-grade machine learning solutions.
• Strong foundation in machine learning and deep learning, including model development, evaluation, and optimisation.
• Proficient in Python, with hands-on experience in machine learning frameworks such as PyTorch and scikit-learn, as well as computer vision libraries such as OpenCV.
• Experience in deploying and maintaining ML services, including API development using Flask, FastAPI, or Node.js, and containerisation using Docker.
• Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), retrieval optimisation, and graph databases will be advantageous.
• Self-motivated and proactive, with strong ownership, stakeholder management, and communication skills.
• Ability to mentor team members and collaborate effectively across technical and business teams.

(EA Reg No: 20C0312)