Europe Bank | AI ENGINEER | AI & ML SOLUTIONS | INNOVATIVE DIGITAL TRANSFORMATION | GLOBAL PROJECTS

BGC GROUP PTE. LTD.; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A dynamic technology company in Singapore is seeking a highly skilled Machine Learning / AI Engineer to join their team. This position involves designing, building, and deploying end-to-end machine learning solutions with a focus on both traditional ML and generative AI models. Candidates should have a strong background in the ML lifecycle and MLOps practices. The role offers autonomy, exciting projects, and a competitive salary up to $10K per month.

Qualifications

• 8+ years of experience in software development, data science, and ML, with at least 3+ years in AI engineering.
• Strong proficiency in Python with knowledge of ML libraries (Pandas, scikit-learn, TensorFlow, PyTorch, etc.).
• Proven experience with MLOps tools and CI/CD pipelines.

Responsibilities

• Lead the development and deployment of ML models into production.
• Collaborate with CloudOps, DevOps, IT, and security teams.
• Document model performance and governance checkpoints.

Skills

Machine Learning Lifecycle

Python

MLOps

Data Engineering

CI/CD

Education

Degree or Master’s in AI, ML, or Data Science

Tools

MLflow

Kubeflow

Docker

Kubernetes

Job description

Roles & Responsibilities

We are seeking a highly skilled and proactive Machine Learning / AI Engineer to join a dynamic team working on innovative, global AI projects. The ideal candidate will have extensive experience in designing, building, and deploying end-to-end machine learning solutions, particularly in Traditional ML and GenAI models. This hands‑on role involves creating scalable, production‑grade ML systems, ensuring compliance with AI governance standards, and collaborating with cross‑functional teams to drive AI advancements. The position offers autonomy, the opportunity to work on cutting‑edge technologies, and exposure to impactful, international projects.

📍Location : Nearest MRT (Tanjong Pagar)

🕒 Working Hours : Mon–Fri, Office Hours

💰 Salary : Up to $10K / month

🗓 Start Date : Jan 2026

📅 Duration : Permanent

Job Scope

AI & ML Solutions: Design, build, and deploy end-to-end machine learning models for global projects, utilizing both traditional ML and GenAI techniques (e.g., LLMs).

Collaborate & Innovate: Work closely with business stakeholders to understand AI use cases and define AI solutions, driving Proof of Concept (PoC) initiatives.

Engineer & Deploy Models: Build scalable, production‑grade ML systems and deploy them using MLOps best practices (model versioning, monitoring, CI / CD).

Data Engineering: Develop data pipelines, ensure model scalability and maintainability, and automate data exploration and feature engineering processes.

Compliance & Standards: Ensure adherence to AI governance, regulatory standards, and internal compliance protocols while working with stakeholders across the business.

Main Responsibilities

Lead the development and deployment of ML models into production using tools like MLflow, Airflow, Kubeflow, etc.

Collaborate with CloudOps, DevOps, IT, and security teams to integrate ML solutions across platforms.

Document model performance, governance checkpoints, and risk assessments for AI solutions.

Work on automating model retraining and monitoring performance for long‑term optimization.

Conduct research on emerging ML technologies and implement them into scalable solutions.

Requirements

Degree or Master’s in AI, ML, or Data Science with a proven track record in designing and developing ML models.

8+ years of experience in software development, data science, and ML, with at least 3+ years in AI engineering.

Expertise in end-to-end ML lifecycle, including model development, deployment, and monitoring.

Strong proficiency in Python with knowledge of ML libraries (Pandas, scikit-learn, TensorFlow, PyTorch, etc.).

Familiarity with NoSQL databases (experience in Graph databases is a plus).

Proven experience with MLOps tools (e.g., MLflow, Kubeflow) and CI / CD pipelines (Docker, Kubernetes).

Understanding of AI governance, model risk management, and regulatory compliance.

Preferred Skills

Experience with Responsible AI frameworks and bias / fairness testing.

Exposure to feature stores, model registries, and data versioning.

Knowledge in specialized industries (e.g., banking, healthcare) and data privacy standards.

👉 Apply via MyCareersFuture today!

Only shortlisted candidates will be contacted.

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