Modern Treasury is hiring a
AI Software Engineer (Tech Lead)

Summary

Join Modern Treasury as an AI Software Engineer (Tech Lead) to lead the architecture, development, and operations of AI/ML infrastructure, ensuring state-of-the-art models are seamlessly integrated into production environments.

Requirements

• 10+ years of experience in AI engineering or machine learning infrastructure
• Expertise in AI/ML Ops and ML SDLC
• Collaborative AI Research to Production Experience
• Expert in Modern AI Architectures
• Leadership and Technical Expertise
• Cross-functional Communication

Responsibilities

• Lead and optimize the ML SDLC, ensuring a smooth transition from model research to deployment, integrating CI/CD pipelines, monitoring, and scaling
• Oversee the full lifecycle of AI systems, from model development and experimentation to testing, deployment, and continuous optimization
• Collaborate closely with AI Product Researchers to translate research outcomes into scalable, production-ready AI models
• Build amplifying harnesses and tools to improve research-to-production cycles, allowing researchers to rapidly iterate on models
• Architect and manage robust AI/ML Ops frameworks that handle the training, serving, monitoring, and lifecycle management of models, enabling fast iteration and high reliability
• Establish best practices for AI/ML infrastructure, ensuring operational excellence in production environments
• Lead the design of scalable architectures that support both real-time inference and large-scale model training
• Optimize performance and scalability across distributed AI systems, leveraging cloud technologies (e.g., AWS SageMaker, EKS, and distributed computing frameworks)
• Lead innovation initiatives, pushing the envelope on AI-driven systems such as LLMs, transformers, and recommendation engines
• Enable MLOps best practices, incorporating automation for model versioning, rollback, and monitoring to ensure robustness and compliance in production environments
• Partner with engineering, product, and data teams to ensure that AI solutions are fully integrated into product features, driving measurable business outcomes
• Mentor and lead engineering teams, establishing a strong culture of technical excellence, collaboration, and innovation
• Facilitate the seamless integration of research-grade AI models into production, ensuring performance, scalability, and alignment with business requirements