Machine Learning Engineer

22 hours ago


Singapore ARROWPOINT INVESTMENT PARTNERS (SINGAPORE) PTE. LTD. Full time

**About this role**

We are on the lookout for a Junior Machine Learning Engineer who will play a key role in enhancing our Machine Learning capabilities, focusing on innovative solutions for systematic strategies. This role is not just about technical expertise but also about aligning with our forward-thinking vision and being at the forefront of shaping our AI strategy.

**Key Responsibilities**

**ML Engineering and Operations**:

- Develop, implement and optimize predictive models using machine learning and deep learning / AI techniques.
- Deploy, maintain and monitor production models on AWS

**ETL & Data Management**:

- Design and develop efficient ETL pipelines to process and manage large volumes of financial data and alternative data.
- Ensure data integrity and accuracy across various data sources.

**Cloud Computing**:

- Utilize Cloud services to deploy and manage machine learning models in a scalable and reliable manner (Terraform, AWS ECS, Docker, CI/CD pipelines).
- Optimize Cloud resources for performance and cost-effectiveness.

**End-to-End Solution Development**:

- Engage in the complete lifecycle of model development, from data collection and preprocessing to model deployment and monitoring.

**Innovation & Creativity**:

- Explore and implement innovative techniques to solve complex financial problems.
- Stay current with the latest advancements in machine learning and data science to continually improve and innovate.

**Result-Oriented Approach**:

- Focus on delivering high-impact results.Communicate findings and recommendations effectively to senior stakeholders.

**Qualifications**
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Statistics, Mathematics, or a related field.
- 1-3 years of hands-on experience in data science and machine learning (exposure to financial markets in a professional context in a plus).
- Proficiency in Python and relevant libraries (e.g., scikit-learn, Polars, PyTorch).
- Experience with AWS services (e.g., S3, ECS, Lambda, Athena, CloudWatch, etc.).
- Strong understanding of Data platform ETL processes and tools.
- Excellent problem-solving skills and a creative mindset.
- Strong communication and collaboration skills.



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