What We’re About: 

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. 

What Your Work Looks Like

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.

 

Responsibilities

• Lead the design and development of end-to-end AI/ML solutions for algorithmic trading and financial data analysis

• Master basic trading/financial knowledge such as technical analysis and how the stock market works
• Research and study topics related to trading, time-series forecasting, and related fields

• Define modeling strategies, experimentation frameworks, and evaluation methodologies

• Design and implement robust data pipelines for large-scale, high-frequency, and unstructured financial data

• Research and evaluate advanced techniques (e.g., time-series modeling, deep learning, reinforcement learning, quantitative strategies) and apply them to production use cases

• Optimize model performance, stability, and latency for real-world trading environments

• Architect and productionize ML systems with a focus on scalability, monitoring, versioning, and reliability (MLOps best practices)

• Conduct backtesting, simulation, and performance analysis of trading models

• Lead technical discussions, review code and model design, and ensure engineering best practices across the team

• Mentor junior engineers and contribute to team capability development

• Collaborate cross-functionally with data engineers, software engineers, and business stakeholders

• Present technical findings, trade-offs, and recommendations to both technical and non-technical audiences
     

Preferred Requirements & Competencies

• Bachelor’s degree or higher in Computer Engineering, Data Science, AI, Quantitative Finance, or related fields

• 5+ years of experience in machine learning, data science, or AI system development

• Strong experience building and deploying ML models in production environments

• Deep understanding of machine learning fundamentals, statistics, and model evaluation

• Experience with Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.

• Experience designing scalable data pipelines and working with large datasets

• Familiarity with MLOps practices (model versioning, monitoring, CI/CD, containerization, cloud deployment)

• Strong problem-solving skills and ability to diagnose complex model or system performance issues

• Experience with time-series data, quantitative modeling, or reinforcement learning is a strong advantage

• Knowledge of financial markets, trading systems, technical indicators, or portfolio strategies is a big plus

• Excellent communication skills and ability to lead technical initiatives

 

What We Value

• Strong ownership and ability to drive projects independently from concept to production

• Technical leadership and willingness to mentor others

• Curiosity, critical thinking, and a research-driven mindset

• Ability to balance research innovation with practical business impact

• Collaborative mindset with a focus on continuous improvement