AI Engineer
- Central Region, Singapore
- $4,000-6,000 per month
- Permanent
- Full-time
- Proactively identify and engage with high-value business opportunities and potential clients who can significantly benefit from advanced AI and machine learning solutions. Deeply understand client business challenges, pain points, and strategic goals, translating them into clear, solvable AI/ML problems.
- Design end-to-end AI solutions, articulating compelling value propositions and the strategic roadmap for adoption.
- Conduct in-depth assessments of client data infrastructure, data governance, data quality, and overall data maturity.
- Make expert judgment calls on data "AI-readiness" and provide actionable recommendations for data improvement, gap identification, and strategic data capitalization opportunities.
- Rapidly develop functional AI prototypes and Proof-of-Concepts (POCs) that are architecturally sound, adhere to best practices for maintainability, and are designed for production.
- Continuously research and evaluate the latest AI advancements, including Generative AI, Large Language Models (LLMs), Deep Learning, and MLOps methodologies. Synthesize findings into actionable insights, influencing our company's strategic roadmap, service offering development, and contributing to industry thought leadership through presentations to leadership and external forums (moderate to high emphasis).
- Collaborate effectively with the internal AI Production team, ensuring prototypes and solution designs are well-documented, understood, and seamlessly integrated into the full development lifecycle.
- Clearly define the business case, expected return on investment (ROI), and measurable benefits of proposed AI/ML implementations, simplifying complex technical concepts for non-technical audiences.
- Minimum Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field. Master's or Ph.D. preferred.
- At least 5+ years of progressive experience in AI/ML solution design, data science, or AI engineering, with a significant portion in a client-facing or consulting capacity.
- Proven experience in designing, developing, and deploying functional AI/ML prototypes that demonstrate business value and are engineered for production.
- Expert proficiency in Python and extensive experience with core AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Demonstrated hands-on experience with Generative AI and Large Language Models (LLMs), including frameworks like LangChain, for designing and prototyping novel applications.
- Strong practical experience with Google Cloud Platform (GCP) services relevant to AI/ML (e.g., Vertex AI, BigQuery, Cloud Storage, Dataflow, Cloud Functions).
- Proficiency with Docker for containerization and a foundational understanding of container orchestration (e.g., Kubernetes concepts for GKE).
- Solid understanding of MLOps principles for reproducibility, experiment tracking (e.g., MLfl ow, Vertex AI ML Metadata/Model Registry), and model versioning.
- High-level expertise in data governance frameworks, data quality assessment (including tools/libraries like Great Expectations), metadata management (e.g., Google Cloud Data Catalog), and data architecture principles.
- Strong expertise in distributed computing and parallel processing techniques is vital for handling large-scale AI workloads.
- A proven track record of innovations and executions in deep learning, demonstrated through shipping products or first-author publications at leading AI conferences, is a strong differentiator.
- Experience in the container shipping industry or related logistics/supply chain domains is highly advantageous.
- Excellent presentation, documentation, and stakeholder management skills.