Lead AI/ML Engineer

AppZen is the leader in autonomous spend-to-pay software. Its patented artificial intelligence accurately and efficiently processes information from thousands of data sources so that organizations can better understand enterprise spend at scale to make smarter business decisions. It seamlessly integrates with existing accounts payable, expense, and card workflows to read, understand, and make real-time decisions based on your unique spend profile, leading to faster processing times and fewer instances of fraud or wasteful spend. Global enterprises, including one-third of the Fortune 500, use AppZen's invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses. To learn more, visit us at About the Role: We are looking for a Lead AI/ML Engineer to come and work on our growing AI stack. You will be working with a team of highly skilled and motivated data scientists and machine learning engineers. If you are excited about natural language understanding and machine translation, AppZen is the right place for you to apply and grow your skills. Key Responsibilities Technical Leadership: Lead a team of AI/ML engineers, providing technical guidance, mentorship, and code reviews to ensure the delivery of high-quality, scalable solutions. System Architecture: Drive the end-to-end design and architecture of robust, production-grade AI/ML systems. This includes selecting the right technologies, designing data pipelines, and optimizing for performance and cost. LLM & Generative AI Integration: Spearhead the integration of state-of-the-art LLMs and generative AI models. You'll be responsible for strategies around model fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and the full lifecycle management of these models in a production environment. MLOps & Production Engineering: Architect and manage advanced MLOps pipelines for continuous integration, continuous delivery (CI/CD), model serving, monitoring, and automated retraining. You'll ensure the reliability, scalability, and efficiency of all ML services. Cross-functional Collaboration: Work closely with product managers, software engineers, and data scientists to translate business requirements into technical solutions and seamlessly integrate AI/ML models into our core platforms. Required Skills & Experience: Deep Expertise: You must have 5 years of experience building and deploying AI/ML solutions in a professional environment, with a strong portfolio of production systems. System Design: Proven ability to architect and design complex, large-scale software systems that incorporate AI/ML components. You should have a strong understanding of distributed systems, microservices, and system-level performance optimization. Programming & Frameworks: Expert proficiency in Python , Golang and deep, hands-on experience with ML frameworks like PyTorch or TensorFlow. A deep understanding of modern architectures such as Transformers is a must. MLOps & DevOps: Extensive experience with MLOps and DevOps tooling. You must be proficient with Docker and Kubernetes for containerization and orchestration, and have a solid understanding of CI/CD pipelines (e.g., Jenkins, GitLab CI). Experience with cloud-based ML platforms (AWS SageMaker, GCP Vertex AI) is a plus. Communication: Excellent written and verbal technical communication skills. You can articulate complex technical concepts and present data-driven conclusions to both a technical team and executive leadership. Mentorship: Proven experience mentoring and leading junior engineers, helping them grow their skills and careers. Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

---