Role Details: Swift execution of Big Data processing, Machine Learning and ML Ops best practice terabytes of data from the largest Australian retail is what this role is about. Working as part of the ML Development chapter and closely collaborating with Data Scientists, be prepared to build Cloud based cutting edge ML platforms, pipelines and experiment with Big Data and ML tech available on the market.
The team has a culture of its own, which involves an innate desire to do things differently trying to find the best solution for business needs and push tech to the limit. No matter how experienced you are, be prepared to learn a lot!
The primary goal of this role is to help design and build a state of the art Machine Learning. Platform working collaboratively with Data Scientists and other ML developers. The role will report to a Machine Learning Chapter Lead. There is an option to be located in the company's Surry Hills or Norwest offices in Sydney with additional work from home options available.
Hands-on technical leadership in design and implementation of state of the art Machine Learning platform
Growth of ML chapter capability through pioneering new tech and approaches to improve time to market, reliability and performance of Data Science products
Mentoring less experienced ML developers
Stakeholder management across different disciplines
Bachelor or above degree in Computer Science
Commercial software development experience
Good communication and stakeholder management skills
Strong Python and SQL
Kubernetes and Argo/Kubeflow experience will be advantageous
Solid knowledge of data structures, algorithms and system design with focus on reliable high throughput batch and streaming solutions
Solid experience with streaming technologies like Kafka, Pubsub or Kinesis will be advantageous
Practical knowledge of various classes of ML algorithms, techniques and packages
Experience of designing and implementing complex cloud solutions
Experience of building production grade ML feature stores, model stores or ML pipelines in GCP or AWS
GCP Cloud Engineer or above level of certification
Solid ML Ops, SRE or DevOps experience
For more information please feel free to contact email@example.com