Remote AI Engineering Tech Lead

Summary

Join Modern Treasury as an Applied AI Engineer Tech Lead and lead efforts to design, build, and optimize AI-driven solutions for fintech products. This role requires a strong background in applied AI research, with 7-10+ years of industry experience in machine learning, particularly recommendation systems, NLP, and information retrieval.

Requirements

• Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field
• 7-10+ years of industry experience in applied machine learning
• Strong knowledge and hands-on experience in building modern recommendation engines
• Experience with NLP techniques, including working with transformer models, language generation, and other cutting-edge advancements
• Proven experience working with open-source deep learning models (e.g., BERT, GPT, etc.) and scalable training/serving infrastructure (e.g., TensorFlow, PyTorch, Kubernetes, etc.)
• Proficiency in deploying machine learning models in production environments, including experience with MLOps best practices
• Strong programming skills in Python, with experience in machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn)
• Familiarity with cloud-based AI services (e.g., AWS, GCP, Azure)
• Strong ability to collaborate with product managers, founders, and software engineers to build and iterate on product-focused AI solutions
• Proven track record of applying research to solve real-world, large-scale problems in production

Responsibilities

• Lead the end-to-end development and deployment of AI systems, focusing on recommendation engines, NLP, and information retrieval for fintech products
• Drive innovation by identifying new opportunities to apply machine learning to enhance customer experience and product functionality
• Collaborate with engineers and product managers to translate product requirements into sophisticated, scalable AI models
• Oversee the architecture, training, and serving of open-source and proprietary deep learning models using state-of-the-art infrastructure
• Conduct applied product research to evaluate and integrate the latest AI and machine learning techniques into production systems
• Develop, maintain, and optimize machine learning pipelines and frameworks for high-throughput, low-latency model serving
• Ensure AI solutions adhere to regulatory standards and fintech best practices