In short
As a Senior Machine Learning Engineer, you'll build and automate production-level machine learning pipelines to drive our marketing programs at On. You'll partner with business, marketing, and data science teams to design, test, and deploy robust and scalable solutions. You will ensure our models are reliable and effectively integrated into our marketing technology stack.
In the dynamic landscape of On Data, Machine Learning and AI play a crucial role in accelerating our business growth and operations. We are enhancing our technology landscape to fuel the growth of On, helping to ignite the human spirit through movement.
Your Mission
- Drive impact through AI: Collaborate with data scientists to translate models into production-grade machine learning services that drive strong business impact through our marketing technology stack (e.g., email service providers, ad platforms, app platforms).
- Platform excellence: Design, build, and maintain scalable and reliable data and model pipelines. Build an ML Ops infrastructure that monitors model performance and implement alerting to ensure high availability and accuracy.
- Data culture: Work with cross-functional teams to understand business requirements and needs, and translate these into technical plans. AI/ML Best Practices: Contribute to the development of our MLOps best practices and infrastructure.
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Your story
- Technical Acumen: 6+ years of experience in implementing complex machine learning initiatives and independently designing production grade end to end ML/AI pipelines (e.g. Kubeflow, MLflow, Airflow). You have strong programming skills in Python.
- Deep Machine Learning Expertise: You have a strong theoretical foundation and practical expertise in areas such as deep learning, embeddings, clustering models, and prediction.
- AI platform Experience: You are familiar with the core components of AI platforms and have experience in working with production grade AI platforms and components (e.g. Vertex AI, Docker, Kubernetes).
- Cloud and Platform Expertise: You are have experience with cloud-based machine learning platforms (e.g. GCP, AWS).
- Team player: To be successful you will need to partner with a range of data science and engineering team members. You have strong communication and interpersonal skills, allowing you to effectively convey complex technical information to diverse audiences.
- Gen AI: Experience deploying Generative AI a plus
About the Team
You will be part of a growing and diverse team of data engineers, data scientists and product managers passionate about revolutionizing how we leverage AI/ML to solve complex challenges across On. We are building innovative machine learning solutions to optimize internal processes, enhance customer experiences, and drive business growth in areas ranging from e-commerce to supply chain optimisation.
About the Team video
Gioia
Head of Operations Project Portfolio Management
My journey has evolved for sure and, actually, change can lead to infinite possibilities. Those core values that were there when I joined are still here today and I really find them extraordinary every day.
Vivek
Director of Engineering
We’re closely connected to the whole business. Every day, we’re making quick decisions to improve the customer experience. Because these live changes impact the whole business, we deeply respect individual opinion and what others think about the end customer experience.
What we offer
On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically – to stay active, to learn, explore and innovate. Our distinctive approach combines a supportive, team-oriented atmosphere, with access to personal self-care for both physical and mental well-being, so each person is led by purpose.
On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.
What to expect
We want to set everyone up for success, so here’s the lowdown on how we hire. Our process is a two-way street – bringing you into our culture, while helping us learn how you think.
Our full process can last about eight weeks from application to offer, because we care about getting it right. These steps explain how we usually do things.
Before you get started, feel free to consider if you want to work with us. Strange question? Well, we give people a lot of space to navigate their day-to-day and that style isn't for everyone. We want you to be passionate about what you do and be sure this is the right fit. Because when skills and passion combine – it creates that 'Wow' moment.