Machine Learning Engineer 2

Your Journey at Crowe Starts Here: At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That’s why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry. Job Description: About the Role • You will be responsible for developing and maintaining scalable APIs and Kubernetes environments that support the deployment and operation of AI and machine learning models at Crowe. Your role is crucial in ensuring that our AI solutions are robust, efficient, and meaningfully transform business offerings. • Design and development of backend services supporting AI workloads, including REST/gRPC APIs, job orchestration, asynchronous task processing, data/model lifecycle management, and service-to-service communication. • Design, build, and maintain scalable and robust APIs that integrate with Crowe’s machine learning models. • Deploy and manage Kubernetes environments to ensure the reliable operation of our AI systems. • Collaborate with Machine Learning Engineers teams to take AI solutions from Proof of Concept to production readiness. • Implement system architectures that support scaling and distributed computing needs. • Ensure the stability and security of AI deployments through design and execution of rigorous testing and monitoring. Required Skills • 4-8 years’ experience maintaining production-grade APIs. • Software engineering experience in a production environment, with a strong background in system design and architecture. • Expertise in programming languages such as Python and JavaScript. You’re experienced writing scalable, production-level code sufficient to thoroughly review code and mentor on general programming best practices. • Solid understanding of scaling strategies and distributed computing principles. • Demonstrated interface savviness, including experience creating and interacting with RESTful HTTPS API's, websockets, and webhooks. • Experience with at least one Cloud Computing platform (experience with Microsoft Azure a plus). • Experience with serverless functions Preferred Skills • Power Platform, Azure AI Studio, and other Microsoft stack exposure for AI solution deployment. • Certified Kubernetes Application Developer (CKAD) certification or similar credentials. • Demonstrated commitment to DevOps best practices and continuous improvement. • You want to stay fresh with regards to practicing engineering.