Lead Machine Learning Engineer

at  nib Group

LET’S TALK ABOUT WHO WE ARE

The nib Group has a mission and vision of people enjoying better health. Through our success, we aspire to more prosperous and sustainable communities, not only the creation of enterprise value. nib is a trusted health partner, helping members and travellers make more informed healthcare decisions, transact with healthcare systems and generally live healthier lives.
We’re looking for people who share this passion and want to be a part of a team that has the appetite and ambition to be extraordinary. Extraordinary comes in different perspectives and experiences. We’re committed to an environment where everyone has the autonomy and freedom to be their authentic selves, every day.

LET’S TALK ABOUT YOU

With a previous track record of taking nebulous projects, architecting solutions, delegating tasks and ultimately getting things done efficiently, other skills and experience that will set you up for success include:

• Architectural mindset with demonstrated knowledge of software engineering principles.
• An ability to communicate effectively with non-engineers of varying levels at the company including coaching both technical and non-technical skills.
• Strong experience with programming languages, techniques and frameworks aligned with machine learning e.g., Python, Scala, R, Keras, fast.ai and ML platforms e.g., Databricks or Amazon SageMaker.
• Commercial experience developing solutions in modern languages e.g., Python, Node.JS/Typescript, Ruby and/or Golang.
• Experience with relational databases and NoSQL databases.
• Experience with cloud platforms, micro-services, and serverless architectures (ideally AWS) and deployments, including devOps and CI/CD experience.
• Experience designing and building good ML engineering practices e.g., automated testing, continuous integration and continuous delivery.
• Experience creating and deploying product machine learning and data science models with knowledge of end-to-end data scientist workflows.
• Experience with Generative AI, Prompt Engineering and Large Language Models will be highly desirable.

At nib, we recognise that some people may only apply when their education, skills and/or experiences are identical to what an employer is looking for in a candidate. We’re always on the lookout for curious individuals who will add to the culture at nib Group - so if this role resonates with you, please apply!

LET’S TALK ABOUT THIS ROLE

As the Lead Machine Learning Engineer, you will work at the intersection of technology and business, driving innovation and automation cross nib Group using Machine Learning to solve complex business challenges. You will use your business acumen to get the job done, and champion opportunities to use valuable AI & ML based solutions (e.g., Generative AI, Prompt Engineering and Language Learning Models) across the business.

Some other key responsibilities of the role include:

• Leading machine learning engineering initiatives, working with IT and business stakeholders all the way from ideation and business case generation, delivering protypes through to production and ongoing maintenance.
• End-to-end responsibility for projects of increasing complexity, including contributing to common code bases and standards.
• Managerial responsibility for ML engineers and providing technical mentorship for the overall team by removing blockers, drafting clear time schedules, and assisting more junior members of the team.
• Building solutions and delivery plans that align to business objectives and constraints and iterating on these during execution.

With a previous track record of taking nebulous projects, architecting solutions, delegating tasks and ultimately getting things done efficiently, other skills and experience that will set you up for success include:

• Architectural mindset with demonstrated knowledge of software engineering principles.
• An ability to communicate effectively with non-engineers of varying levels at the company including coaching both technical and non-technical skills.
• Strong experience with programming languages, techniques and frameworks aligned with machine learning e.g., Python, Scala, R, Keras, fast.ai and ML platforms e.g., Databricks or Amazon SageMaker.
• Commercial experience developing solutions in modern languages e.g., Python, Node.JS/Typescript, Ruby and/or Golang.
• Experience with relational databases and NoSQL databases.
• Experience with cloud platforms, micro-services, and serverless architectures (ideally AWS) and deployments, including devOps and CI/CD experience.
• Experience designing and building good ML engineering practices e.g., automated testing, continuous integration and continuous delivery.
• Experience creating and deploying product machine learning and data science models with knowledge of end-to-end data scientist workflows.
• Experience with Generative AI, Prompt Engineering and Large Language Models will be highly desirable