Principal Machine Learning Engineer

Job Description:

• Engage with business leaders and teams to understand workflows, challenges, and goals
• Identify AI opportunities and define successful solution outcomes
• Lead cross-functional teams in converting ambiguous opportunities into well-scoped AI initiatives
• Set priorities, technical approaches, success measures, and paths from proof of concept to enterprise adoption
• Architect and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms
• Own consequential technical work hands-on
• Evaluate feasibility and business value through practical experimentation
• Address data readiness, integration, user experience, security, compliance, performance, cost, and operational needs
• Define scalable architectures and create reusable components, documentation, decision records, and handoff materials
• Provide technical direction for product and platform teams developing successful proofs of concept into enterprise solutions
• Establish engineering standards through technical leadership and mentorship
• Guide design decisions, strengthen delivery practices, and help teams navigate uncertainty

Requirements:

• Doctorate degree and 2 years of Machine Learning Engineer experience; or Master's degree and 6 years of Machine Learning Engineer experience; or Bachelor's degree and 8 years of Machine Learning Engineer experience; or Associate's degree and 10 years of Machine Learning Engineer experience; or High school diploma / GED and 12 years of Machine Learning Engineer experience
• Substantial experience in machine learning and software engineering, including senior technical ownership of applications that progressed beyond a prototype or pilot
• Deep full-stack development skills
• Python proficiency
• Experience developing APIs, application back ends, user interfaces, and data integrations
• Experience with modern software design practices
• Hands-on experience with cloud platforms such as AWS
• DevOps experience including Terraform or similar infrastructure as code, containers, CI/CD, automated deployment, and observability
• Strong practical knowledge of generative AI and machine learning application design
• Experience with model selection, evaluation, inference, and trade-offs among managed services, open-source tools, and custom implementations
• Experience with enterprise architecture and integration patterns
• Knowledge of access controls, secure handling of sensitive data, reliability, performance, and maintainability
• Experience establishing evaluation approaches for AI applications using quantitative and qualitative evidence
• Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and AI development tools
• Demonstrated technical leadership through architecture decisions, mentorship, and collaboration across business, product, engineering, security, and platform teams
• At least 2 years of experience directly leading teams, projects, or programs, or directing resource allocation
• Clear written and verbal communication skills
• Experience presenting technical options and trade-offs to technical and business audiences

Benefits:

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
• Group medical, dental and vision coverage
• Life and disability insurance
• Flexible spending accounts
• A discretionary annual bonus program
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible
• Career development opportunities
• Work/life balance support
• Financial plans with opportunities to save towards retirement or other goals