Portfolio Manager

MCP (Switzerland) Sàrl

Baar

Presencial

CHF 180 000 - 320 000

Tempo integral

Há 8 dias

Uma candidatura completa num minuto

Currículo e carta de apresentação personalizados, prontos a enviar.

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Resumo da oferta

Millennium in Zug, Switzerland seeks a highly experienced Portfolio Manager to lead quantitative trading initiatives using agentic AI and ML. You will manage risk, optimize live trading strategies, and collaborate with a global team to translate research into production-ready systems.

The role emphasizes autonomous decision-making, human-AI collaboration, and strong fundamentals in finance and risk control within a cutting-edge AI-driven trading environment.

Qualificações

  • Master’s or Ph.D. in a quantitative field (CS, Math, Physics, Statistics, Engineering)
  • Minimum 10 years of Python-based development including ML model development
  • Experience with building agentic AI frameworks
  • Deep knowledge of planning, tool use, memory, reflection and collaboration in agentic systems
  • Experience applying genetic algorithms for adaptive systems (selection, crossover, mutation, fitness)
  • Experience tuning hyperparameters and training processes for genetic algorithms
  • Familiarity with financial markets and willingness to learn portfolio management including P&L responsibility and risk management

Responsabilidades

  • Focus on machine learning and agentic systems to manage a live trading book with autonomous reasoning to solve complex problems
  • Interact with cognitive planning, memory, reflection, and collaboration components to support autonomous decision-making in quantitative trading
  • Fine-tune genetic algorithms to optimize system performance and contribute to deep learning model development for PM layers
  • Own portfolio management responsibilities: take risk, manage P&L, and trade within defined risk parameters
  • Build and customize agentic workflows and tools for trading strategies
  • Contribute to machine learning model development for PM applications
  • Develop training routines and hyperparameters tuning for adaptive models
  • Execute human-in-the-loop checks to ensure trading strategies meet acceptance criteria

Conhecimentos

Python
ML frameworks
Agentic AI frameworks
Genetic algorithms
Portfolio risk management
P&L responsibility

Formação académica

Master's or PhD in quantitative field

Ferramentas

Python
Agentic AI tools

Descrição da oferta de emprego

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.

Employer: MCP (Switzerland) GmbH

Job Title: Portfolio Manager

Office Location: Zug, Switzerland

Meet the Team

We are seeking a Portfolio Manager to manage risk and generate returns while utilizing cutting-edge machine learning and agentic AI solutions within our Quantitative Trading divisions. This role sits at the intersection of Portfolio Management and Artificial Intelligence, requiring active engagement with autonomous cognitive systems for strategy development.

What You’ll Do
  • Focus on machine learning and agentic systems to manage a live trading book while working with cognitive reasoning architectures that enable autonomous systems to solve complex financial problems and reason through multi-step solutions.
  • Utilize and interact with agentic systems, including planning algorithms, memory architectures, reflection mechanisms, and collaborative reasoning patterns that support autonomous decision‑making in quantitative trading environments.
  • Fine‑tune genetic algorithms hyperparameters to optimize adaptive system performance, decision‑making quality, and contribute to deep learning model development for the PM model layer and custom agentic workflows.
  • Responsible for portfolio management: take risk, manage P&L, and make trading decisions within defined risk parameters while developing expertise in quantitative portfolio management principles.
  • Utilize agentic systems, deploying and working with cognitive reasoning systems for quantitative modeling problems, leveraging planning, tool use, memory, reflection, and collaboration capabilities.
  • Contribute to machine learning model building for PM model layer applications specific to portfolio management objectives.
  • Build and customize agentic workflows and tools tailored to portfolio management needs and specific trading strategies.
  • Execute human‑in‑the‑loop decisions and checks ensuring that traded strategies meet quant trading acceptance criteria

This position combines portfolio management with cutting‑edge agentic AI technology. Your work will directly impact:

  • Research‑to‑production cycles for quantitative strategies
  • Complex, multi‑step financial workflows through autonomous systems
  • Enhanced decision‑making through human‑AI collaboration
What You Bring
  • Master’s or Ph.D. degree in a quantitative field (Computer Science, Mathematics, Physics, Statistics, Engineering, or related discipline)
  • Minimum of 10 years of experience with Python‑based development, including machine learning model development.
  • Experience with building agentic AI frameworks.
  • Deep knowledge of the core capabilities of agentic systems: planning, tool use, memory, reflection, and collaboration.
  • Experience applying genetic algorithm methodologies to develop adaptive systems that evolve and improve through selection, crossover, mutation, and fitness‑based optimization.
  • Experience adjusting hyperparameters and tune training processes for genetic algorithms.
  • Familiarity with financial markets and a willingness to learn portfolio management discipline, including P&L responsibility and risk management.
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