Machine Learning Engineer
Rezolve AI2 months ago
Remote, Singapore or Singapore, SingaporeEntry Level
Responsibilities
- Design, develop, optimize, evaluate, monitor, and improve machine learning models.
- Build representative training datasets to improve model accuracy, fairness, and performance.
- Develop scalable tools, workflows, and automation for model development and operational efficiency.
- Partner with Product, Engineering, and Data teams to design and deploy production-ready machine learning solutions.
- Improve internal platforms, data pipelines, and analytical capabilities.
- Communicate technical findings and recommendations to technical and non-technical stakeholders.
- Stay current with machine learning, generative AI, and applied AI technologies.
Requirements
- Strong experience developing and deploying machine learning models in production environments is preferred.
- Proficiency in Python and machine learning libraries such as Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow.
- Experience evaluating model performance and driving continuous improvement.
- Strong analytical, problem-solving, collaboration, and communication skills.
- Passion for artificial intelligence, machine learning, and solving real-world customer problems.
- Fresh graduates with a strong machine learning foundation are welcome to apply.
- Preferred qualifications include production ML deployment at scale, computer vision, deep learning, large language models, cloud-native production systems, ML model inference, e-commerce or retail technology, and AI-powered search experience.
- A PhD or master’s degree in Computer Science, Electronic Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field is a plus.
Benefits
- Opportunity to work at a fast-growing global company focused on AI-powered commerce.
- Collaborative team environment working on technologies affecting millions of users globally.
- Opportunity to contribute significantly to AI innovation and product strategy.
- Inclusive, diverse, and equal-opportunity work environment.
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