{"id":43117,"date":"2026-02-27T17:48:57","date_gmt":"2026-02-27T10:48:57","guid":{"rendered":"https:\/\/loolootech.com\/?post_type=job&p=43117"},"modified":"2026-03-24T15:06:02","modified_gmt":"2026-03-24T08:06:02","slug":"senior-machine-learning-engineer-project-algorithmic-trading","status":"publish","type":"job","link":"https:\/\/loolootech.com\/th\/job\/senior-machine-learning-engineer-project-algorithmic-trading\/","title":{"rendered":"Senior Machine Learning Engineer (Project Algorithmic Trading)"},"content":{"rendered":"
What We\u2019re About:\u00a0<\/b><\/h5>\n

At Looloo, we believe that deep technology will play an increasingly important role in defining the future of all industries. We are driven by a strong passion to solve the challenging problems facing the world today by developing innovative solutions that can lay a foundation for a better tomorrow.\u00a0<\/span><\/p>\n

What Your Work Looks Like<\/b><\/h5>\n

As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of advanced AI\/ML systems for algorithmic trading. You will lead a small close-knit team that focuses on creating profitable trading algorithms. This role requires strong technical leadership, deep understanding of data engineering, ML techniques, and the ability to drive projects end-to-end from research to production.<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Responsibilities<\/b><\/h5>\n
    \n
  • Lead the design and development of end-to-end AI\/ML solutions for algorithmic trading and financial data analysis<\/span><\/li>\n
  • Master basic trading\/financial knowledge such as technical analysis and how the stock market works<\/span><\/li>\n
  • Research and study topics related to trading, time-series forecasting, and related fields<\/span><\/li>\n
  • Define modeling strategies, experimentation frameworks, and evaluation methodologies<\/span><\/li>\n
  • Design and implement robust data pipelines for large-scale, high-frequency, and unstructured financial data<\/span><\/li>\n
  • Research and evaluate advanced techniques (e.g., time-series modeling, deep learning, reinforcement learning, quantitative strategies) and apply them to production use cases<\/span><\/li>\n
  • Optimize model performance, stability, and latency for real-world trading environments<\/span><\/li>\n
  • Architect and productionize ML systems with a focus on scalability, monitoring, versioning, and reliability (MLOps best practices)<\/span><\/li>\n
  • Conduct backtesting, simulation, and performance analysis of trading models<\/span><\/li>\n
  • Lead technical discussions, review code and model design, and ensure engineering best practices across the team<\/span><\/li>\n
  • Mentor junior engineers and contribute to team capability development<\/span><\/li>\n
  • Collaborate cross-functionally with data engineers, software engineers, and business stakeholders<\/span><\/li>\n
  • Present technical findings, trade-offs, and recommendations to both technical and non-technical audiences<\/span>
    \n<\/span>\u00a0\u00a0\u00a0<\/span><\/li>\n<\/ul>\n
    Preferred Requirements & Competencies<\/b><\/h5>\n
      \n
    • Bachelor\u2019s degree or higher in Computer Engineering, Data Science, AI, Quantitative Finance, or related fields<\/span><\/li>\n
    • 5+ years of experience<\/b> in machine learning, data science, or AI system development<\/span><\/li>\n
    • Strong experience building and deploying ML models in production environments<\/span><\/li>\n
    • Deep understanding of machine learning fundamentals, statistics, and model evaluation<\/span><\/li>\n
    • Experience with Python and ML frameworks such as <\/span>TensorFlow<\/b>, <\/span>PyTorch<\/b>, <\/span>Scikit-learn<\/b>, etc.<\/span><\/li>\n
    • Experience designing scalable data pipelines and working with large datasets<\/span><\/li>\n
    • Familiarity with MLOps practices (model versioning, monitoring, CI\/CD, containerization, cloud deployment)<\/span><\/li>\n
    • Strong problem-solving skills and ability to diagnose complex model or system performance issues<\/span><\/li>\n
    • Experience with time-series data, quantitative modeling, or reinforcement learning is a strong advantage<\/span><\/li>\n
    • Knowledge of financial markets, trading systems, technical indicators, or portfolio strategies is a big plus<\/span><\/li>\n
    • Excellent communication skills and ability to lead technical initiatives<\/span><\/li>\n<\/ul>\n

       <\/p>\n

      What We Value<\/b><\/h5>\n
        \n
      • Strong ownership and ability to drive projects independently from concept to production<\/span><\/li>\n
      • Technical leadership and willingness to mentor others<\/span><\/li>\n
      • Curiosity, critical thinking, and a research-driven mindset<\/span><\/li>\n
      • Ability to balance research innovation with practical business impact<\/span><\/li>\n
      • Collaborative mindset with a focus on continuous improvement<\/span><\/li>\n<\/ul>\n

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