Lead Machine Learning Engineer

7+ years of professional experience in machine learning and software engineering. At least 2 years in a formal or informal leadership capacity. Proven ability to architect and deploy scalable, production-grade ML solutions on a major cloud platform (GCP is a significant asset). Hands-on experience with Infrastructure-as-Code tools (e.g., Terraform). Designing for distributed computing. Deep, hands-on expertise in Python for backend ML systems. Mastery of software engineering best practices (e.g., clean architecture, robust testing, CI/CD). Design and build REST APIs (e.g., using Flask/FastAPI). Proficient in SQL for complex data manipulation. Exceptional ability to communicate complex technical concepts to diverse audiences. Excel at leading technical discussions, presenting solutions, and mentoring teammates.

Act as the lead technical authority in high-stakes engagements. Partner with commercial team to architect winning solutions. Lead the delivery of enterprise-grade systems. Design end-to-end ML architectures on GCP. Implement robust MLOps pipelines using Infrastructure-as-Code. Define the technical DNA of our ML practice. Spearhead the development of internal accelerators and reusable frameworks. Formally mentor and coach junior and mid-level engineers.