3 months ago
Singapore, SingaporeMid Level
Responsibilities
- Use AI engineering, delivery, and governance expertise to solve complex problems and deliver transformative outcomes for clients and citizens.
- Contribute to Temus's AI and data team.
- Develop and maintain relationships with clients, colleagues, and partners across varied contexts.
- Continuously build and extend relevant technical knowledge and skills.
- Develop and deploy LLM, agentic AI, or machine learning solutions end to end.
- Support responsible AI evaluation, model deployment, monitoring, retraining, and related MLOps activities.
Requirements
- At least 3 years of relevant experience in artificial intelligence, machine learning, data science, or software engineering.
- At least one hands-on end-to-end AI development and deployment project.
- At least 3 years of implementation experience with serverless computing, CI/CD, containerization, infrastructure as code, code version control, and automated testing.
- Exposure to AWS, Azure, or GCP.
- Hands-on experience with LLMs, agentic tooling, prompt engineering, fine-tuning, and responsible AI evaluation for AI Engineering-focused candidates.
- Hands-on experience with ML development, deployment, experiment tracking, training workflows, and MLOps for ML Engineering-focused candidates.
- Knowledge of NLP, computer vision, recommendation systems, reinforcement learning, or time series forecasting is relevant to the ML Engineering track.
- Exposure to multi-agent systems, tool use, RAG pipelines, autonomous task execution, or MLOps lifecycle practices is desirable.
Tech Stack
AnsibleAWSAzureDatadogDockerGoogle Cloud PlatformHugging Face TransformersKubernetesMLflowPyTorchscikit-learnTensorFlowTerraform
Categories
