Applied AI Engineer (Tech Lead)

$200,000 - $360,000/Yr

Modern Treasury - San Francisco, CA

Full-time - Senior

San Francisco, CA

About the position

The Applied AI Engineering Tech Lead will spearhead the design, development, and optimization of AI-driven solutions that enhance customer experiences and the Modern Treasury platform. This role involves leveraging advanced machine learning models to create recommendation systems, improve information retrieval, and advance natural language processing (NLP) within the fintech sector. The position requires collaboration with cross-functional teams to translate research into scalable products, making a significant impact on the company's operations.

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.

Requirements

• Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 7-10+ years of industry experience in applied machine learning, with demonstrated success in leading projects in the fields of recommendation systems, NLP, and information retrieval.
• 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 using research to solve real-world, large-scale problems in production.

Benefits

• Generous benefits package
• Company equity