ML / AI Jobs in Singapore
There are 293 open ML / AI jobs in Singapore on freehire right now. 97 of them were posted recently. The skills employers ask for most often are machine-learning, ai and python.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| SGD | month | SGD 8,750 | SGD 12,000 | SGD 16,875 | 31 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- machine-learning 93%
- ai 76%
- python 75%
- pytorch 46%
- llm 42%
- cloud 33%
- tensorflow 31%
- deep-learning 29%
How the work is done
- Onsite 52 · 18%
- Remote 31 · 11%
- Hybrid 13 · 4%
Visa sponsorship offered in 64% of the 11 postings that state a position on it.
Seniority
- Senior 42
- Intern 22
- Junior 21
- Lead 14
- Principal 14
- Staff 9
Who is hiring
- 1000+ employees 40
- 501-1000 employees 3
- 11-50 employees 2
- 51-200 employees 1
Machine Learning Research & Engineering Specialist
Remote, worldwide, part-time (~15 hrs/week) research-level ML engineering role at a consultancy: the hire builds, debugs, and optimizes ML training and inference pipelines and numerical code in Python, uses coding agents in the workflow, and validates correctness and performance for an advanced AI training project.
Machine Learning Engineer 1
About the Role Abnormal AI is seeking a Machine Learning Engineer - I (MLE) to join the Misdirected Email Detection (MED) team. The MED team plays a critical role in preventing accidental data loss by detecting and…
(Staff/ Sr. Staff) Machine Learning Engineer
Description: Lead applied research and strategic definition of machine learning algorithms, quantization methodologies, and toolchain capabilities for the Neural Network Development Kit (NDK) roadmap targeting…
Device Modeling AI/ML Software Engineer
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create…
Senior ML/AI Engineer - #1733
Key Responsibilities • MLOps/AIOps Platform Engineering: Design and implement reusable platform components and golden paths for experiment tracking, model registry, pipeline orchestration, deployment, monitoring,…
Senior ML/AI Engineer - #1731
Key Responsibilities • Agentic AI Architecture: Design the end-to-end architecture for FAM agentic AI solutions, including agent orchestration, workflow design, state management, tool integration, human approval points…
(Staff/ Sr. Staff) Machine Learning Engineer
Description: Lead applied research and strategic definition of machine learning algorithms, quantization methodologies, and toolchain capabilities for the Neural Network Development Kit (NDK) roadmap targeting…
ML/AI Engineer (Fraud Analytics Model) - Government Project
Role Overview The ML/AI Engineer is embedded within Data Analytics and AI Division (DSAD), working as part of the division's Fraud Analytics Model (FAM) team. The role supports FAM 2.0, which detects misuse of public…
Senior Software Engineer, Machine Learning Platform
How you'll make impact You’ll build and scale the machine learning platform that powers risk decisioning across Airwallex, helping teams develop, deploy, monitor, and improve models that protect every dollar moving…
Apple Media Products - Machine Learning Engineering Manager
Innovate at Apple. Lead in Singapore. Our engineers have created some tough acts to follow, and they continue to lead us to innovative breakthroughs. Because they’re driven not by what would be easy, but by what would…
Member of Technical Staff, Machine Learning
Build and deploy core ML components for an AI-native assistant that automates daily tasks with high reliability and low latency using Python, PyTorch/JAX, and GPU-based production systems.
Applied Machine Learning Engineer
Builds and owns end-to-end ML systems for a proactive AI assistant, focusing on long-running workflows, reliability, and real-world task completion using PyTorch/JAX and GPU infrastructure.
Machine Learning Engineer, Ranking & Retrieval
Build and improve the ML systems behind an AI-native mobile communication app — working on classification, ranking, retrieval, personalization and evaluation from model development through production deployment. Stack centers on Python, PyTorch/JAX, embeddings and vector search.
Technical Lead, Machine Learning
Hands-on ML technical lead owning the end-to-end machine learning stack — data pipelines, training/fine-tuning, evaluation, inference, and deployment — behind AI-native productivity apps. Remote role based in China; core stack is Python, PyTorch/JAX, and GPU-based training and inference systems.
Principal Machine Learning Engineer
Principal ML Engineer building AI-native productivity apps for tasks and workflows. Responsible for the end-to-end ML lifecycle, including training pipelines, evaluation systems, and high-performance GPU inference using Python, PyTorch, or JAX. Focuses on turning research into reliable, scalable production systems for long-running workflows.
Lead Engineer, Machine Learning
The Lead Engineer, Machine Learning will build and scale production-ready AI systems, managing the full model lifecycle from training to deployment. The role focuses on creating reliable, high-performance inference systems using Python, PyTorch, and JAX to power proactive, AI-native applications.
Staff Machine Learning Engineer
Staff ML Engineer owning the end-to-end ML execution layer at an AI-native productivity startup — building training/fine-tuning pipelines, evaluation systems, and high-performance GPU inference to turn large models into reliable production systems for proactive everyday apps (email, notes, tasks, calendar). Stack: Python, PyTorch/JAX, GPU infra.
Machine Learning Engineer
工作說明 AICS (https://aics.asus.com/) is a newly formed organization incubating applied AI services that can leverage ASUS' large portfolio of hardware products to unlock a new generation of smart products and services.…
Senior Software Engineer, Machine Learning, Debug - Singapore
Build and deploy deep-learning models to analyze mosquito images, count pupae, and optimize release strategies for disease eradication using computer vision and ML.