AI ML Engineer

AI/ML Engineer

Company: Consulting Firm, Singapore, Singapore (On-site)

A global leader in management and IT consulting, specializing in strategy, process engineering, and technology-enabled transformation. They partner with businesses to create tailored solutions for complex challenges, leveraging innovative and human-centric approaches to deliver long-term value. The company’s mission is to bridge the gap between strategy and execution through cutting-edge technology and expertise.

Job Overview:

The AI/ML Engineer will focus on deploying Machine Learning (ML) models and data pipelines into production environments while ensuring performance and reliability. This role also involves developing backend services, managing databases, and utilizing cloud platforms to deliver scalable solutions.

Key Responsibilities:

• Deploy ML models and data pipelines into production environments.
• Design, develop, and maintain backend services for data and ML.
• Optimize database management systems and ensure efficient operations.
• Utilize cloud platforms (e.g., AWS) for deploying scalable applications.
• Automate model training, testing, and deployment processes using CI/CD pipelines.
• Develop and implement metrics to evaluate the effectiveness of ML models.

Required Qualifications:

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• Minimum 5 years of experience in backend development and relational database management.
• Proficiency in cloud services, particularly AWS.
• Hands-on experience with Python and ML libraries such as Pandas and PyTorch.
• Expertise in database query languages like SQL.
• Familiarity with CI/CD tools (e.g., Jenkins).
• Experience with containerization technologies like Docker.
• Ability to work collaboratively within multidisciplinary teams comprising data scientists, software engineers, and product managers.
• Comfortable working in Agile development environments.

Preferred Qualifications:

• Knowledge of AWS machine learning services such as Textract and Comprehend.
• Experience with workflow orchestration tools like Dagster or Airflow.
• Familiarity with Snowflake for data warehousing.
• Exposure to Azure OpenAI API for advanced AI capabilities.