Advanced Support Worker Jobs in New Zealand
Canonical
MLOps Field Engineer
- Posted 4d ago
- Remote
- Full Time
Job Description
Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few roles based in offices. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution.
The company is founder led, profitable and growing.
We are hiring an MLOps Field Engineer to help global companies embrace AI/ML in their business, using the latest open source capabilities on public and private cloud infrastructure, Linux and Kubernetes. Our team applies expert insights to real-world customer problems, enabling the enterprise adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC and related analytics, machine learning and data technologies. We are working to create the world's best open source data platform, covering traditional SQL databases and today's NoSQL data stores, as well as the machinery which turns data into insights and executable models.
The people who love this role are MLOps engineers who enjoy customer conversations and solving customer problems during the presales cycle. They are solutions architects who like to solve customer problems through architecture, presentations and training. This role is highly focused on designing ML architectures for external customers. It is not a software development role.
This role is particularly suited to candidates with a technical background who are business minded and driven by commercial success. This role is on our global Field Engineering team and will work closely with enterprise sales leads. We are specifically looking for people interested in solving the most difficult problems in modern data architectures. Training LLMs on multiple K8s clusters deployed on a hybrid cloud infrastructure with GPU sharing across multiple teams? Processing 10M events in real time for financial transactions? Object detection on 10k parallel 4K video streams? These are the problems we solve day to day.
Location: Most of our colleagues work from home. We are growing teams in EMEA, Americas and APAC time zones, so can accommodate candidates from almost any country.
What your day will look like
The global Field Engineering team members are Linux and cloud solutions architects for our customers, designing private and public cloud solutions fitting their workload needs. They are the cloud consultants who work hands-on with the technologies by deploying, testing and handing over the solution to our support or managed services team at the end of a project. They are also software engineers who use Python to develop Kubernetes operators and Linux open source infrastructure-as-code.
- Work across the entire Linux stack, from kernel, networking, storage, to applications
- Architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack, and Spark
- Deliver solutions either on-premise or in public cloud (AWS, Azure, Google Cloud)
- Collect customer business requirements and advise them on Ubuntu and relevant open source applications
- Grow a healthy, collaborative engineering culture in line with the company values
- Deliver presentations and demonstrations of Ubuntu Pro and AI/ML capabilities to prospective and current clients
- Liaise with product teams to give them feedback on requirements to influence roadmap
- Work collaboratively with your sales team to reach our common targets
- Global travel up to 30% of time for internal, external events and customer meetings
What we are looking for in you
- Exceptional academic track record from both high school and university
- Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path
- Experience in data engineering, MLOps, or big data solutions deployment
- Experience with a relevant programming language, like Python, R, or Rust.
- Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation
- Track record of going above-and-beyond expectations to achieve outstanding results
- Demonstrated personal interest in continuous learning and development
- Practical knowledge of Linux, virtualisation, containers and networking
- Business-minded technology thinker and problem solver
- Knowledge of cloud computing concepts & leaders, such as Kubernetes, AWS, Azure, GCP
- Interest in large-scale enterprise open source - private clouds, machine learning and AI, data and analytics
- Intermediate level Python programming skills
- Passion for technology evidenced by personal projects and initiatives
- The work ethic and confidence to shine alongside motivated colleagues
- Professional written and spoken English with excellent presentation skills
- Experience with Linux (Debian or Ubuntu preferred)
- Excellent interpersonal skills, curiosity, flexibility, and accountability
- A dynamic person who loves to jump in new projects and interact with people
- Appreciative of diversity, polite and effective in a multi-cultural, multi-national organisation
- Thoughtfulness and self-motivation
- Result-oriented, with a personal drive to follow up and meet commitments
- Ability to travel internationally, for company events up to two weeks long, and customer or industry meetings
What you’ll learn
- Architect and deploy AI/ML infrastructures, data processing pipelines and multi-cluster distributed training
- Wide range of open source applications and skills
- Work directly with customers in a range of different businesses
- Real-life and hands-on exposure to a wide range of emerging technologies and tools
What we offer colleagues
We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
- Distributed work environment with twice-yearly team sprints in person
- Personal learning and development budget of USD 2,000 per year
- Annual compensation review
- Recognition rewards
- Annual holiday leave
- Maternity and paternity leave
- Employee Assistance Programme
- Opportunity to travel to new locations to meet colleagues
- Priority Pass, and travel upgrades for long haul company events
About Canonical
Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.
Canonical is an equal opportunity employer
We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.
Hard Skills Required
- Data Engineering, MLOps or Big Data Solutions Deployment Experience
- Linux
- Cloud Computing Concepts and Leaders
- Python Programming Skills
Soft Skills Required
- Collaboration Skills
- Troubleshooting Skills
- Communication Skills
- Result-Oriented
Job Schedule
- Shift Work
Company Video
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