Machine Learning Engineer

3 days ago

Singapur, 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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