Mlops Engineer

Who you are

You are an MLOps engineer with a passion for helping global companies leverage AI and machine learning in their operations. You enjoy engaging with customers and solving their challenges during the presales cycle, using your technical expertise to guide them through architecture and implementation. Your experience with open source technologies, particularly in cloud environments, positions you as a trusted advisor in the field. You thrive in a collaborative environment, working with diverse teams across the globe to deliver innovative solutions.

You have a strong background in Linux and Kubernetes, which are essential for deploying and managing machine learning workflows. Your familiarity with tools like Kubeflow and MLflow allows you to streamline the process of model training and deployment, ensuring that data-driven insights are readily available to your clients. You are comfortable discussing technical concepts with both technical and non-technical stakeholders, making you an effective communicator in any setting.

Desirable

Experience with data analytics and machine learning frameworks is a plus, as it enhances your ability to provide comprehensive solutions to clients. Familiarity with various data storage solutions, including SQL and NoSQL databases, will further strengthen your contributions to the team. You are eager to learn and adapt to new technologies, continuously improving your skill set to stay ahead in the rapidly evolving field of MLOps.

What you'll do

As an MLOps Field Engineer at Canonical, you will play a crucial role in helping enterprises adopt AI and machine learning technologies. You will engage with clients to understand their specific needs and challenges, providing tailored solutions that leverage the latest open source capabilities. Your responsibilities will include designing and implementing machine learning workflows on public and private cloud infrastructures, ensuring that clients can effectively utilize their data to drive business outcomes.

You will collaborate closely with engineering teams to integrate machine learning models into existing systems, facilitating seamless deployment and operation. Your expertise in tools like Kubeflow and MLflow will be instrumental in optimizing the model lifecycle, from training to deployment and monitoring. You will also conduct training sessions and presentations for clients, empowering them to maximize the value of their AI initiatives.

Your role will involve staying up-to-date with industry trends and advancements in machine learning and data technologies, allowing you to provide informed recommendations to clients. You will contribute to the development of best practices and documentation, ensuring that knowledge is shared across the team and with clients. Your ability to think critically and solve complex problems will be essential as you navigate the challenges of implementing AI solutions in diverse environments.

What we offer

Canonical offers a dynamic work environment where you can thrive as part of a global team. You will have the opportunity to work remotely, collaborating with colleagues from various countries and cultures. The company values diversity and inclusion, fostering a workplace where everyone can contribute their unique perspectives. You will be part of a mission-driven organization that is committed to open source software and its impact on the world.

We encourage you to apply even if your experience doesn't match every requirement. Canonical is dedicated to supporting your professional growth, providing resources and opportunities for continuous learning. Join us in shaping the future of AI and machine learning in the enterprise space, and make a meaningful impact on how organizations leverage technology to achieve their goals.