Singapore, Singapore
Live, first seen by us 85 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
As an Analyst, AI/ML, you will play a crucial role in the development and implementation of cutting-edge Generative AI solutions that address significant business challenges.
Develop and implement Proof of Concepts (PoCs) prototypes for AI/ML and Generative AI solutions, ensuring alignment with business objectives.
Develop and implement PoC prototypes for AI/ML and Generative AI solutions
Write clean, well-documented code for data processing, model training, and deployment
Run experiments to evaluate model performance and optimize algorithms for scalability
Integrate solutions into existing systems and platforms with the Engineering team
As an Analyst, AI/ML, you will play a crucial role in the development and implementation of cutting-edge Generative AI solutions that address significant business challenges. This role focusses on hands-on implementation, rapid prototyping, and collaboration with cross-functional teams to deliver innovative solutions that address real business challenges. Your contributions will directly impact our strategic goals, driving innovation and excellence in customer interactions.
Develop and implement Proof of Concepts (PoCs) prototypes for AI/ML and Generative AI solutions, ensuring alignment with business objectives.
Develop and implement Proof of Concepts (PoCs) prototypes for AI/ML and Generative AI solutions
Write clean, efficient, and well-documented code for data processing, model training, and deployment
Conduct experiments to evaluate model performance and optimize algorithms for scalability
Collaborate with the Engineering team to integrate solutions into our existing systems and platforms
- Actively participate in technical discussions and forums across Amex - Advanced degree (Master/ PhD) in quantitative discipline (e.g., Computer Science, Engineering, Statistics, Mathematics). - Strong programming skills in at least one language (Python, Java, C++, etc.)
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Day 85
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Well past American Express’s usual: its jobs come down by about day 8.
From 5,297 similar postings that came down, and 293 of American Express’s. Coming down is not always a hire.
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- Advanced degree (Master/ PhD) in quantitative discipline (e.g., Computer Science, Engineering, Statistics, Mathematics). - Strong programming skills in at least one language (Python, Java, C++, etc.) - Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data processing libraries
- Strong programming skills in at least one language (Python, Java, C++, etc.) - Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data processing libraries - Extensive experience in machine learning, NLP and Generative AI, with a demonstrated ability to build scalable prototypes from inception to solution.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
You will be part of an energetic A.I./Machine Learning cross-functional team, collaborating with various business/product partners (e.g. Credit, Fraud, Risk, Web, Mobile, Marketing, Enterprise Automation, etc.) to drive a cohesive set of solutions enabling the ever-growing strategic capabilities in the AI field.
Role Overview:
As an Analyst, AI/ML, you will play a crucial role in the development and implementation of cutting-edge Generative AI solutions that address significant business challenges. This role focusses on hands-on implementation, rapid prototyping, and collaboration with cross-functional teams to deliver innovative solutions that address real business challenges. Your contributions will directly impact our strategic goals, driving innovation and excellence in customer interactions.
Develop and implement Proof of Concepts (PoCs) prototypes for AI/ML and Generative AI solutions, ensuring alignment with business objectives.
Write clean, efficient, and well-documented code for data processing, model training, and deployment.
Collaborate with the Technology team to integrate solutions into our existing systems and platforms.
Conduct experiments to evaluate model performance and optimize algorithms for scalability.
Stay abreast of the latest trends in AI/ML and actively share knowledge and insights to contribute to the collective growth and technical proficiency of the team.
Collaborate with the Engineering team to integrate solutions into our existing systems and platforms, enhancing functionality and user engagement.
Actively participate in technical discussions and forums across Amex
Advanced degree (Master/ PhD) in quantitative discipline (e.g., Computer Science, Engineering, Statistics, Mathematics).
Strong programming skills in at least one language (Python, Java, C++, etc.)
Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data processing libraries
Extensive experience in machine learning, NLP and Generative AI, with a demonstrated ability to build scalable prototypes from inception to solution.
Proven expertise in applying deep learning and NLP techniques to solve complex problems, with a portfolio of projects on real-world problems.
Solid understanding of Large Language Models and practical experience with Generative AI
Strong ability to translate real-world problems to data science problems.
Excellent communication and collaboration skills, with the ability to collaborate effectively with both technical and non-technical teams.
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Singapore, Singapore
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