AI Engineer

TOPPAN ECQUARIA PTE. LTD.; Singapore; Presencial; SGD 60 000 - 90 000; Tempo integral

Resumo da oferta

TOPPAN ECQUARIA PTE. LT D. is seeking an AI Solutions Engineer to design, build, and deploy scalable AI and generative AI solutions for enterprise clients in Singapore.

You will work with stakeholders to translate requirements into practical AI architectures, leveraging LLMs, AI agents, and open-source models, and ensure secure, scalable deployment across cloud platforms.

Qualificações

• Bachelor’s degree in a related technical field.
• 2–3 years in Data Science or AI/ML roles.
• Experience designing, deploying AI solutions including LLMs and generative models.
• Strong knowledge of ML, NLP, and transformer-based models (GPT, BERT).
• Proficiency in Python and ML frameworks; cloud deployment experience.

Responsabilidades

• Design, develop, and implement scalable AI and generative AI solutions for enterprise use cases.
• Contribute to AI solution architecture including models, frameworks, APIs, and cloud services.
• Collaborate with stakeholders to translate requirements into technical solutions.
• Develop and integrate AI solutions leveraging LLMs, generative AI, AI agents, and open-source models.
• Integrate AI solutions with APIs, databases, and platforms such as Azure OpenAI and Hugging Face.
• Develop end-to-end AI pipelines for data processing, model development, deployment, and monitoring.
• Implement RAG, vector databases, similarity search, and optimization techniques.
• Conduct research and evaluate emerging AI technologies for enterprise use cases.
• Establish evaluation methods for quality, accuracy, relevance, and performance.
• Ensure AI solutions adhere to security, privacy, scalability, and responsible AI practices.

Conhecimentos

ML/NLP expertise

Transformer models

Data preprocessing

Stakeholder communication

Problem-solving

Formação académica

Bachelor's degree in Computer Science, Engineering, Data Science, AI or related

Ferramentas

Python

PyTorch

TensorFlow

LangChain

LlamaIndex

CrewAI

AutoGen

Azure

AWS

GCP

Descrição da oferta de emprego

Responsibilities

• Design, develop, and implement scalable AI and generative AI solutions for enterprise use cases.
• Contribute to AI solution architecture, including the selection of appropriate models, frameworks, APIs, cloud services, and technologies.
• Collaborate with business stakeholders, domain experts, and clients to understand requirements and translate them into practical technical solutions.
• Develop and integrate AI solutions leveraging LLMs, generative AI, AI agents, and open-source models.
• Integrate AI solutions with APIs, enterprise applications, databases, and platforms such as Azure OpenAI and Hugging Face.
• Develop and optimise end-to-end AI pipelines covering data processing, model development, deployment, and monitoring.
• Implement RAG, vector databases, similarity search, and other techniques to improve AI application performance and information retrieval.
• Conduct research, proof-of-concepts, and evaluations of emerging AI technologies for enterprise applications.
• Establish appropriate evaluation methods to assess the quality, accuracy, relevance, and performance of AI solutions.
• Ensure AI solutions adhere to appropriate security, privacy, scalability, and responsible AI practices.

Prerequisites

• Bachelors Degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related discipline.
• Minimum 2-3 years of experience in Data Science, Machine Learning, Artificial Intelligence, or related fields.
• Experience designing, developing, integrating, and deploying AI solutions, including LLMs, generative AI, AI agents, and/or open-source AI models.
• Strong knowledge of machine learning, deep learning, NLP, generative AI, and Transformer-based models such as GPT and BERT.
• Proficiency in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, CrewAI, or AutoGen.
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in cloud environments.
• Experience with APIs, databases, vector databases, RAG, embeddings, and AI application integration.
• Understanding of solution architecture principles, system integration, scalability, security, and performance optimisation.
• Knowledge of data engineering practices, including data preparation, cleaning, preprocessing, and pipeline development.
• Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• Strong communication and stakeholder management skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• Passion for AI innovation and the ability to stay current with emerging AI technologies and industry trends.