Applied Machine Learning Engineer (Remote or Nelson HQ)

Shuttlerock is the pre-eminent provider of beautiful ad creative worldwide and is now on a mission to create the best video ad ordering and delivery platform in the world. We’re looking for an Applied Machine Learning Engineer to join our team and play a key role in this growth by applying their passion for ML to the creative industry.

Our Generative AI team is empowered to solve customer and business problems using cutting-edge tools and processes. Our team is cross-functional, comprising a product owner, analysts, and engineers. As a Machine Learning Engineer you will be responsible for developing and deploying ML models that will keep Shuttlerock on the cutting edge of creative production, and providing specialist knowledge and high level technical support.

That this is a remote-friendly role, within +/- 4 hours of New Zealand Standard Time (NZST).

What you'll do

Your success as a Machine Learning Engineer will come from:

• Developing, testing, and refining ML models.
• Designing and building efficient operational architectures for our ML applications.
• Applying MLOps principles to data science workflows, in order to build resilient, reproducible training pipelines.
• Automating repeatable processes, to iteratively improve the efficiency of our ML workflows.
• Developing and implementing a strategy for the storage of models and training data.
• Keeping abreast of new developments in the ML space, and embracing emerging technologies.

You will be joining a global design & technology company of wonderful, talented and ambitious people that is experiencing rapid growth and is backed by a fantastic team of local and global investors.

What you'll bring

• At least two years experience of building and training ML models.
• A degree in ML engineering, computer science, mathematics, or similar discipline (postgraduate research a plus)
• Fundamental software engineering skills (eg. the ability to implement a well-structured code base, CI/CD, monitoring, logging, version control).
• Familiarity working within containerised or virtual environments.
• Solid programming skills in at least one high-level language, such as Python.
• Experience using MLOps best-practises to design, develop and deploy ML workflows.
• Experience training, versioning and productionizing ML models, ideally working with GANs, VAEs, or autoregressive models. If you have not encountered Stable Diffusion yet, you’ll be excited to learn.
• Pragmatic and platform-agnostic.
• Passionate about technology and working on the cutting edge.

Additionally, experience in (or willingness to learn about):

• ML technologies such as Amazon Sagemaker, Google AI Platform, ML API Services, PyTorch, Scikit-Learn etc.
• Model optimization and parallelization.
• Deploying models at scale.
• Experience working with IaC technologies such as Terraform.
• Proven ability to work with Python, using a git-based pull request workflow.

As part of the Shuttlerock team you will have the chance to work remotely while still working with the big global names in innovation such as Facebook, Instagram, Google, and Youtube - just to name a few. 

With offices around the globe including New York, Berlin, Singapore, and Tokyo, Shuttlerock recognises the value that a diverse and inclusive workplace brings and the innovation it breeds. We actively seek people from diverse backgrounds, life experiences, education and cultures so please be prepared to share how your unique perspective will help our product teams and Shuttlerock grow.