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AI Engineer

Temus
Singapore3w ago

About the role

<div class="content-intro"><p><span data-teams="true"><em>Temus is a Temasek-backed consulting firm providing digital transformation solutions for the private and public sectors. W</em><em>e aspire to be a strategic partner in realising the Singapore Government’s Smart Nation vision. We are headquartered in Singapore and have more than 400 employees across a wide range of disciplines in strategy, design, architecture, technology, data &amp; AI.</em></span></p></div><p><strong>Your Role</strong></p> <ul> <li>Harness your expertise in AI engineering, delivery, and governance to solve complex problems and deliver transformative change for clients and citizens.</li> <li>Make an outstanding contribution to a world-class AI and data team.</li> <li>Develop and maintain relationships with a broad range of clients, colleagues, and partners across a variety of contexts and formats.</li> <li>Invest continuously in building and extending your knowledge and skills.</li> </ul> <p><strong>Your Background</strong></p> <ul> <li>At least 3 years of relevant working experience in fields related to artificial intelligence, machine learning, data science, or software engineering.</li> <li>Completed at least one hands-on AI development and deployment end-to-end.</li> <li>Exposure to agentic AI concepts such as multi-agent systems, tool-use, RAG pipelines, or autonomous task execution is highly desirable.</li> <li>At least 3 years of implementation experience with serverless computing, CI/CD, containerisation, Infrastructure as Code, code version control and automated testing.</li> <li>Exposure to one or more cloud services: AWS, Azure or GCP.</li> <li>Candidates should demonstrate strength in either AI Engineering or ML Engineering (see below). Strength in both is a plus.</li> </ul> <p><u>AI Engineering (LLM &amp; Agentic Systems)</u></p> <ul> <li>Practical hands-on experience with LLMs and agentic tooling: LangChain, LangGraph, AutoGen, CrewAI, OpenAI API, Anthropic API, AWS Bedrock, Google Vertex AI, Azure ML, Hugging Face Transformers, MLFlow, Dataiku, MS Fairlearn, Google PAIR.</li> <li>Experience with prompt engineering, fine-tuning, and responsible AI evaluation.</li> </ul> <p><u>ML Engineering / MLOps</u></p> <ul> <li>Practical hands-on experience with ML development and deployment tooling: Jupyter, PyTorch, TensorFlow, Scikit-learn, AWS SageMaker, MLFlow, Docker, Kubernetes, Terraform, Ansible, Datadog.</li> <li>Broad knowledge of NLP, computer vision, recommendation systems, reinforcement learning and time series forecasting.</li> <li>Exposure to model experiment tracking and training workflows: hyperparameter tuning, experiment logging (e.g. MLFlow, Weights &amp; Biases), and reproducible training runs.</li> <li>Exposure to the MLOps lifecycle: data versioning, model training pipelines, experiment tracking, model registry, deployment, monitoring, and retraining triggers — using tools such as MLFlow, Weights &amp; Biases, Kubeflow, AWS SageMaker Pipelines, Azure ML Pipelines, or Google Vertex AI Pipelines.</li> </ul><div class="content-conclusion"><p>&nbsp;</p> <p><em>Temus is an equal opportunities employer. We welcome applications from all. We do not discriminate by race, religion, belief, ethnicity, origin, disability, age, partnership status, sexual orientation, or gender identity.</em></p> <p><em>We see the diversity of our team as a strategic advantage, and we work actively to maintain it.</em></p> <p><em>By applying for this role, you have read and acknowledge the data privacy statement via this link -&nbsp;<a class="fui-Link ___1rxvrpe f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1hu3pq6 f11qmguv f19f4twv f1tyq0we f1g0x7ka fhxju0i f1qch9an f1cnd47f fqv5qza f1vmzxwi f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn" href="https://www.temus.com/job-applicant-data-protection/" target="_blank">temus.com/job-applicant-data-protection/</a></em></p> <p>&nbsp;</p></div>

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