ML/AI Engineer

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ML/AI Engineer

Singapore

Published at 30/06/2025

We are seeking a ML / AI Engineer to build, test, and support AI-powered solutions. You will collaborate with data scientists and engineers to turn notebooks into production‑ready code, automate pipelines, and integrate ML outputs into business systems. This role suits someone with solid Python coding skills, a good grasp of ML fundamentals, and hands‑on experience with SQL, and cloud‑based data platforms. A great fit for a technically strong developer profile.

Missions

• Model Development & Implementation: Develop and fine‑tune machine learning models for structured, semi‑structured, and unstructured data (e.g., classification, regression, forecasting, clustering).
• Workflow Automation & Pipelines: Support the design and implementation of reproducible ML pipelines, including data preprocessing, model training, testing, and deployment using CI/CD and orchestration tools.
• Cloud Integration & Platform Work: Work with cloud‑native platforms like Snowflake and optionally Databricks, Azure, or AWS to access, prepare, and deliver data and model outputs efficiently.
• Generative AI & Applied NLP: Apply LLMs and GenAI models to tasks such as
  • Summarization of long‑form content (e.g., financial or research reports).
  • Generating textual insights or commentary from structured data.
  • Creating draft visual outputs (charts, highlights) based on underlying analysis.
  • Supporting prompt engineering, RAG workflows, or chatbot integration when needed.
• Applied AI Use Cases: Contribute to a variety of AI‑powered use cases, such as:
  • OCR and document parsing
  • Image classification
  • Time series forecasting
  • Scoring models (e.g., risk, prioritization)
• Cross‑Team Collaboration: Work closely with data scientists, engineers, and business stakeholders to align on data inputs, expected outputs, and use case priorities.
• Reusable Code & Documentation: Develop clean, well‑documented Python code and reusable components that can be leveraged across teams and use cases.
• Learning & Growth: Stay current with evolving trends in GenAI and applied ML; contribute to team learning by exploring and experimenting with new tools and models.

Qualifications

• At least Bachelor’s degree in Computer Science, Data Science, or a related field.
• Proficient in Python with solid understanding of ML libraries (e.g., scikit‑learn, XGBoost).
• Experience working with data using pandas, SQL, and cloud‑based platforms like Snowflake.
• Exposure to CI/CD workflows and an interest in MLOps tools and concepts.
• Familiarity with the end‑to‑end ML lifecycle.
• Strong analytical skills and ability to translate business needs into practical ML solutions.
• Exposure to NLP, LLMs, RAG and GenAI technologies.

Nice To Have

• Experience integrating ML/AI outputs into BI platforms or dashboards.
• Understanding of data governance, privacy, and responsible AI practices.

We offer

• Competitive salary and performance‑based incentives.
• Multinational and fast‑growing team with exciting regional projects.
• Flexible, collaborative, and supportive work environment.
• International exposure and career development opportunities.
• Health and accident insurance.

Our Recruitment Process

• First Round – Initial test & HR Interview: Includes an online logic & personality test to get to know you better prior the HR interview.
• Second Round – Technical Assessment: Your chance to showcase your skills through a focused technical assessment.
• Third Round – Operational Interview: An in-depth conversation with the Line Manager to explore your expertise and fit.
• Final Decision: Internal alignment and, if successful, a formal offer to join the team!