374 AI Engineer jobs in Singapore

Position Overview:

We are seeking a Research and Development Engineer focused on Generative AI Image and Video Algorithm Development . The ideal candidate should have experience in developing and optimizing generative AI algorithms, including but not limited to Stable Diffusion （image or video）, GANs, ControlNet, and LoRA . In particular, expertise is required in portrait generation, 3D depth-aware scenes, and image inpainting , designing efficient generative AI models to address challenges related to image realism, consistency, and harmony , thereby improving overall image quality and optimizing the visual experience.

Responsibilities:

• Research and develop advanced generative AI algorithms for image quality enhancement, focusing on clarity, color consistency, and noise reduction;
• Research and develop advanced generative AI image quality algorithms to enhance imageclarity, realism, consistency, and visual harmony.
• Optimize image generation and rendering quality in portrait and depth-aware scenes, aligning with product application workflows.
• Improve image quality and novel view synthesis in complex depth scenarios, including small objects, motion scenes, and stereo vision.
• Participate in the full algorithm development lifecycle, from prototyping to product deployment, collaborating closely with software and hardware engineering teams to ensure efficient algorithm integration.

Qualification/ Requirements:

• Master’s or Ph.D. degree in Computer Vision, Image Processing, Large Models, or related fields .
• Proven experience in research and development of generative AI image generation algorithms , with proficiency in Stable Diffusion, GANs, ControlNet, LoRA , and model optimization.
• Familiarity with novel view synthesis, depth image generation, and image inpainting models, along with efficient training and data preparation pipelines .
• Proficiency in Python , with experience in PyTorch or other deep learning frameworks.
• Strong capability in developing and optimizing generative AI algorithms to enhance image quality in terms of clarity, realism, consistency, and harmony.
• Prior experience in image generation system development and optimization is a plus, including but not limited to text-to-image generation, conditional generation, image editing, style transfer, image inpainting, super-resolution, and image enhancement.
• Excellent teamwork, communication, and problem-solving skills.

We are looking for a motivated and enthusiastic Junior AI Engineer to join our dynamic team. As a Junior AI Engineer, you will work closely with senior engineers and data scientists to help develop, implement, and optimize AI and machine learning models to solve real-world problems. You will have the opportunity to contribute to various projects, learning and growing within a fast-paced, innovative environment.

Job Description & Requirements Key Responsibilities

•Design and implement scalable ML pipelines for Generative and Agentic AI applications.

•Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.

•Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.

•Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.

•Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).

•Implement and maintain network security protocols to safeguard AI systems and data pipelines.

•Monitor and optimize system performance, reliability, and scalability.

•Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills Required

•Bachelor’s degree in Computer Science, Engineering, or a related field.

•Experience in Machine Learning engineering or AI system integration.

•Hands-on experience with OpenShift, Docker, Kubernetes.

•Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.

•Exposure to data and network security and compliance in AI systems.

•Understanding of Generative AI and Agentic AI concepts.

•Experience with LLM prompt engineering, or RAG pipelines.

•Knowledge of API integration and microservices architecture.

•Proficiency in Python used both for ML and automation tasks

•Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.

•Knowledge of Workflow Orchestrator, such as Ctrl-M

•Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.

•Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

Job Description & Requirements Key Responsibilities

•Design and implement scalable ML pipelines for Generative and Agentic AI applications.

•Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.

•Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.

•Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.

•Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).

•Implement and maintain network security protocols to safeguard AI systems and data pipelines.

•Monitor and optimize system performance, reliability, and scalability.

•Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills Required

•Bachelor’s degree in Computer Science, Engineering, or a related field.

•Experience in Machine Learning engineering or AI system integration.

•Hands-on experience with OpenShift, Docker, Kubernetes.

•Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.

•Exposure to data and network security and compliance in AI systems.

•Understanding of Generative AI and Agentic AI concepts.

•Experience with LLM prompt engineering, or RAG pipelines.

•Knowledge of API integration and microservices architecture.

•Proficiency in Python used both for ML and automation tasks

•Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.

•Knowledge of Workflow Orchestrator, such as Ctrl-M

•Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.

•Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

Job Description & Requirements Key Responsibilities

•Design and implement scalable ML pipelines for Generative and Agentic AI applications.

•Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.

•Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.

•Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.

•Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).

•Implement and maintain network security protocols to safeguard AI systems and data pipelines.

•Monitor and optimize system performance, reliability, and scalability.

•Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills Required

•Bachelor’s degree in Computer Science, Engineering, or a related field.

•Experience in Machine Learning engineering or AI system integration.

•Hands-on experience with OpenShift, Docker, Kubernetes.

•Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.

•Exposure to data and network security and compliance in AI systems.

•Understanding of Generative AI and Agentic AI concepts.

•Experience with LLM prompt engineering, or RAG pipelines.

•Knowledge of API integration and microservices architecture.

•Proficiency in Python used both for ML and automation tasks

•Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.

•Knowledge of Workflow Orchestrator, such as Ctrl-M

•Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.

•Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

We are looking for AI engineer with below requirements;

Key Responsibilities

• Design and implement scalable ML pipelines for Generative and Agentic AI applications.
• Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.
• Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.
• Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.
• Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).
• Implement and maintain network security protocols to safeguard AI systems and data pipelines.
• Monitor and optimize system performance, reliability, and scalability.
• Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills Required

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience in Machine Learning engineering or AI system integration.
• Hands-on experience with OpenShift, Docker, Kubernetes.
• Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.
• Exposure to data and network security and compliance in AI systems.
• Understanding of Generative AI and Agentic AI concepts.
• Experience with LLM prompt engineering, or RAG pipelines.
• Knowledge of API integration and microservices architecture.
• Proficiency in Python used both for ML and automation tasks
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Knowledge of Workflow Orchestrator, such as Ctrl-M
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

We are looking for AI Engineer with below key responsibilites and skills requirements;

Key Responsibilities

• Design and implement scalable ML pipelines for Generative and Agentic AI applications.
• Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.
• Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.
• Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.
• Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).
• Implement and maintain network security protocols to safeguard AI systems and data pipelines.
• Monitor and optimize system performance, reliability, and scalability.
• Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills Required

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience in Machine Learning engineering or AI system integration.
• Hands-on experience with OpenShift, Docker, Kubernetes.
• Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.
• Exposure to data and network security and compliance in AI systems.
• Understanding of Generative AI and Agentic AI concepts.
• Experience with LLM prompt engineering, or RAG pipelines.
• Knowledge of API integration and microservices architecture.
• Proficiency in Python used both for ML and automation tasks
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Knowledge of Workflow Orchestrator, such as Ctrl-M
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

We are seeking a passionate and skilled AI Engineer to join our growing team in Singapore. You will be responsible for designing, developing, and deploying artificial intelligence (AI) and machine learning (ML) models to support our products, services, and business operations.

In this role, you will collaborate with cross-functional teams to solve complex challenges using AI, including data scientists, software engineers, and product managers. You should have a strong foundation in machine learning algorithms, data processing, and software development.

This role offers the opportunity to work on high-impact projects and stay at the forefront of AI innovations in Singapore’s growing tech landscape.

• Design and implement AI and machine learning solutions for business use cases.
• Perform data preprocessing, cleaning, feature selection, and exploratory data analysis.
• Develop, train, validate, and deploy ML/DL models using libraries such as scikit-learn, TensorFlow, or PyTorch.
• Work with Natural Language Processing (NLP) tools for applications such as text summarisation, classification, sentiment analysis, and chatbot development.
• Collaborate with software engineers to integrate AI models into production systems.
• Monitor, maintain, and improve model performance over time.
• Evaluate new technologies, tools, and research to enhance AI capabilities.
• Ensure ethical AI practices, including fairness, privacy, and transparency in AI solutions.
• Prepare technical documentation, model reports, and deployment guides.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, or related fields.

• Strong programming skills in Python (preferred), with experience using AI/ML libraries and frameworks.
• Knowledge of algorithms, statistics, and probability.
• Experience with cloud platforms such as AWS, Google Cloud, or Microsoft Azure.
• Familiarity with MLOps tools (e.g. MLflow, Docker, Git, Airflow) is an advantage.
• Hands-on experience with data handling using SQL, Pandas, or Spark.
• Basic understanding of software engineering practices (CI/CD, REST APIs, version control).

• Good communication and interpersonal skills.
• Strong analytical and problem-solving mindset.
• Ability to work independently and collaboratively in a team.
• Passion for innovation and continuous learning.

• At least 1–3 years of relevant experience in an AI/ML role.
• Experience deploying models in production environments.
• Familiarity with local regulations on data privacy and AI governance (e.g., Singapore PDPA, IMDA AI Governance Framework).
• Participation in AI/ML competitions or open-source contributions is a plus.

• Work on cross-industry AI projects (e.g., FinTech, HealthTech, Retail, Smart Nation).
• Upskilling through sponsored certifications and courses.
• Internal career mobility and advancement to senior AI/ML roles.

Interested candidates may apply directly via MyCareersFuture by submitting your CV, portfolio (if any), and a brief description of your most impactful AI project.