Staff Machine Learning Engineer

About This Role

This Staff Machine Learning Engineer role involves designing and building production-grade, multi-agent AI systems for a growing Fin Tech company. The successful candidate will contribute to advisor copilots, investment intelligence, workflow automation, and autonomous research, working with modern agent frameworks and large language models.

Responsibilities

• Design, develop and deploy production-grade multi-agent AI systems using modern agent frameworks and large language models (LLMs)
• Build intelligent AI workflows that combine context retrieval, reasoning, tool execution, validation and compliance controls
• Develop scalable distributed services for agent orchestration, with a focus on observability, monitoring, resilience and fault tolerance
• Create evaluation frameworks to assess reasoning quality, accuracy, groundedness, hallucination mitigation and financial correctness
• Implement scalable approaches to memory management, context handling and persistent agent state
• Collaborate closely with Product, Design and Engineering teams to translate business requirements into scalable AI solutions
• Continuously optimize AI systems for performance, latency, reliability, scalability and cost efficiency
• Influence the design and evolution of AI infrastructure, including model serving, orchestration, vector databases, caching and cloud-native architecture

Requirements

• At least 6 years of experience in Machine Learning, including 2-3 years building and deploying Generative AI or LLM-powered applications in production environments
• Proven experience designing, developing and implementing production-ready multi-agent AI systems
• Strong expertise in multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine-tuning, agent memory and synthetic data generation
• Advanced Python programming skills with hands-on experience using modern AI and machine learning frameworks
• Experience building distributed systems and deploying cloud-native applications across AWS, Azure or Google Cloud Platform (GCP)
• Strong understanding of AI system monitoring, evaluation frameworks, reliability engineering and model performance optimization
• Demonstrated ability to design scalable, enterprise-grade AI architectures that integrate multiple models, services, and workflows
• Previous experience working in a fast-paced startup or scale-up environment is highly desirable

Benefits

• Comprehensive benefits package

About the Company

Our client is a growing Fin Tech company.