Millennium

Systematic Production Support Engineer

Millennium Singapore

Investment Management · 5,001-10,000 employees

Yesterday
support-engineer Senior (5-10 yrs) Full-time Singapore
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About the role

Build and maintain a scalable platform for trading strategy monitoring, reporting, and operations. Partner with portfolio managers to deliver technical solutions and automate workflows to improve system stability and efficiency.

What they look for

Python Linux Unix PostgreSQL NLP Supervised learning Unsupervised learning Generative AI Low-latency trading Quantitative finance Electronic trading C++ Java Kafka AWS GCP

Requirements

Requires 5+ years of Python development experience in production environments and strong knowledge of Linux/Unix systems. Candidates must have experience with relational databases, low-latency trading environments, and quantitative finance concepts.

Full description

Systematic Production Support Engineer

About Millennium Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Meet the Team Millennium’s Information Technology team is core to the health and growth of the business. The firm’s active, multi-manager model depends on flexible, scalable technology and advanced proprietary systems, including the continued development of next-generation analytical and trading capabilities. Within this environment, the systematic operations and support engineering team partners closely with portfolio management teams to help deliver a reliable, high-performing trading and technology platform with operational excellence at its foundation.

We are looking for an experienced professional to help us scale our systematic operations and support engineering capabilities. This role directly supports portfolio management teams across Millennium, with operational excellence at the core. Our efforts are focused on delivering the highest quality returns to our investors – providing a world-class and reliable trading and technology platform is essential to this mission. This is a unique opportunity to drive significant value creation for one of the world’s leading investment managers.

What You'll Do

  • Build, enhance, and maintain a reliable, scalable, and integrated platform for trading strategy monitoring, reporting, and operations
  • Partner with portfolio managers and internal stakeholders to understand requirements and deliver practical production support solutions
  • Reduce operational risk by implementing monitoring, reporting, and trade workflow tools across trading and operations processes
  • Develop automated systems and workflows that improve the efficiency, stability, and scalability of trading and operational support
  • Streamline development and deployment processes to strengthen release quality and production readiness
  • Implement MCP servers to support the broader Support Engineering team and enable more proactive production monitoring
  • Help maintain a robust production environment that supports systematic trading activity and high service reliability

What You Bring

  • 5+ years of Python development experience in production environments
  • Strong experience working in Linux or Unix environments
  • Hands-on experience with PostgreSQL or other relational databases
  • Ability to understand, discuss, and translate requirements from portfolio managers into effective technical solutions
  • Understanding of NLP, supervised and unsupervised learning, and generative AI models
  • Experience operating and monitoring low-latency trading environments
  • Familiarity with quantitative finance, electronic trading concepts, and financial data across instruments such as equities, futures, and FX
  • Experience building backend or distributed systems and working with technologies such as C/C++, Java, Scala, Go, C#, Kafka, SDLC automation tools, containers, and cloud platforms including AWS, GCP, or Azure

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