Machine Learning Devops Engineer Ii - Sw Job in Crowe Llp

Job Description

About Crowe Horwath IT Services LLP AI

At Crowe Horwath IT Services LLP, we are committed to making the future of human work more purposeful. We achieve this by leveraging state-of-the-art machine learning, modern architectures, and industry experts to create AI-powered solutions that transform the way we do business.

About the Team

We foster good science and are dedicated to supporting your growth as a Machine Learning Engineer (MLE). Our team encourages continuous learning and collaboration through ethics and book club meetings, monthly lightning talks, conference support, and weekly independent time for ongoing skill development. We pride ourselves on maintaining a healthy work-life balance with flexible work-from-home policies. Our distributed team discourages weekend and off-hours work, unless that s genuinely your preference.

About the Role

As a key member of our AI Engineering team, you will be responsible for developing and maintaining scalable APIs and Kubernetes environments that support the deployment and operation of machine learning models. Your work will ensure that our AI solutions are robust, efficient, and transformative for business offerings.

Responsibilities

• Design, build, and maintain scalable and robust APIs to integrate with Crowe s machine learning models.
• Deploy and manage Kubernetes environments to ensure the stable operation of AI systems.
• Collaborate with Machine Learning Engineers to bring AI solutions from Proof of Concept to production readiness.
• Implement system architectures that support scalability and distributed computing needs.
• Ensure the stability and security of AI deployments through rigorous testing and monitoring.

Required Skills

• Experience in software engineering within a production environment, with a strong background in system design and architecture.
• Proficiency in programming languages such as Python and JavaScript, with the ability to write scalable, production-level code.
• Solid understanding of scaling strategies and distributed computing principles.
• Experience creating and interacting with RESTful APIs, websockets, and webhooks.
• Familiarity with at least one Cloud Computing platform (experience with Microsoft Azure is a plus).
• Experience with serverless functions, such as OpenFaaS.

Preferred Skills

• Exposure to Power Platform, Azure AI Studio, and other Microsoft stack tools for AI solution deployment.
• Certified Kubernetes Application Developer (CKAD) certification or similar credentials.
• Commitment to DevOps best practices and continuous improvement.
• A passion for machine learning, with deep knowledge beyond introductory materials like blogs and tutorials.