Machine Learning Engineer

Machine Learning 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.

Our Israel office is located in the Bursa area of Ramat Gan. This role is on-site. As a global firm, proficiency in English is required.

Meet the Team The Information Technology department is core to the health and growth of Millennium’s business. Supporting the firm’s active, multi-manager model, the team develops flexible, scalable technology and advanced proprietary systems, including next-generation analytical, trading, and AI capabilities. Based on-site in Millennium’s Israel office in the Bursa area of Ramat Gan, the team builds and evolves enterprise technology platforms that enable innovation across the firm.

What You'll Do • Lead the development of AI and machine learning capabilities within the infrastructure group across multiple applications. • Transform rapid prototypes into production-grade AI and machine learning systems that deliver measurable business value. • Identify repeatable patterns and technical friction points across Millennium’s AI stack, translating them into reusable capabilities such as LLM routing and dedicated-hardware inference optimization. • Design and implement scalable AI infrastructure that supports federated agent development and distributed deployment across the organization. • Orchestrate AI agents across distributed systems and service buses, ensuring generated code aligns with enterprise architecture standards and best practices. • Build high-performance evaluation pipelines and observability frameworks to assess agentic systems against rigorous accuracy, safety, and latency requirements. • Advance the adoption of AI-augmented development practices by providing technical leadership and integrating AI-powered tools into engineering workflows and CI/CD pipelines. • Partner directly with teams across the firm to teach AI infrastructure best practices and guide successful adoption.

What You Bring • Bachelor’s degree with 6+ years of experience, Master’s degree with 4+ years of experience, or PhD with 2+ years of experience in Computer Science, Data Science, Machine Learning, or a related field. • Experience building or operating AI/ML infrastructure, agent orchestration platforms, or comparable AI-powered development tools. • Proficiency in Python and PyTorch or a similar deep learning framework. • Strong understanding of enterprise software architecture patterns and distributed systems design. • Production experience with Docker, Kubernetes, and container orchestration. • Strong communication and teaching skills, with the ability to partner effectively with teams across the organization as a deployed engineer. • Experience with cloud platforms such as AWS, Azure, or GCP; infrastructure-as-code tools; and MLOps practices, including model training, versioning, deployment, monitoring, drift detection, and performance optimization. • Experience building agentic AI systems using frameworks such as LangGraph, LangChain, or PydanticAI, including LLM integration, tool calling, structured outputs, MCP implementations, vector databases, embedding pipelines, and retrieval-augmented generation architectures.