Senior Machine Learning Engineer / Data Scientist

  • Full Time Job
  • Hybrid

Narrative is one of NZ’s fastest growing software as a service (SaaS) companies. We build products that cater to a market of millions of professional photographers worldwide. Our AI-powered tools help our customers improve their workflows, significantly increasing what they can get done each day. With the backing of top-tier Venture Capitalists and a team of exceptionally talented staff, we are committed to driving innovation in this space.

We have many thousands of photographers using our products and we are growing. This is a unique opportunity to join our team and build industry-leading AI products.  

About the Role:

At Narrative, you'll be working closely with the Head of AI, contributing directly to the core-value of our company. Your work will navigate the highly technical world of world-class ML, while also communicating complex concepts to members of the business with different expertise. The role encompasses every stage of ML model development, from ideation to production. This includes coordinating data labelling, building new custom models, refining existing models to keep up with changing requirements, optimising models to run on-device, retraining models with new data, and meticulously validating models at every phase of their development. 

We have a strong, nurturing company culture at Narrative. You'll join a smart, friendly, and supportive team with psychological safety. Here, we can be our authentic selves, freely discuss ideas, make the best decisions, and do our best work.

Throughout your journey at Narrative, you’ll not only grow in your skills to become an expert in all aspects of what it takes to build impactful ML models, but also contribute to our world-class products, helping to define an entirely new category in the making.

Some of the things you will work on:

  • Designing, training, modifying, validating, optimising and deploying novel ML models in the Computer Vision space
  • Working with a Data Labelling team to refine our training data
  • Building the core ML underlying a new product category
  • Collecting subjective and objective analytics on the performance of models running in the wild
  • Doing statistical analysis on user data and behaviour patterns
  • Enriching our Data Warehouse with insights and classification results
  • Engaging with all parts of the business to understand what to build and why

We’re looking for someone who has:

  • Expertise in building custom Computer Vision ML models in PyTorch or Tensorflow
  • Understanding of how to tune and optimise ML models by improving model structure and training data
  • Outstanding knowledge of data science and statistics principles
  • Deep-seated curiosity and a desire to unearth the root of a problem
  • Ability to interpret and implement findings from academic research papers
  • Proven ability to conduct novel research, particularly in the fields of image processing, mathematical modelling, algorithms, and deep learning
  • Experience equivalent to a BSc (or higher) in Data Science, Computer Science, Software Engineering, Mathematics, or a related field
  • Excellent Python programming skills
  • Experience with data querying for SQL, NoSQL, or Graph databases
  • Exceptional communication skills
  • A scrappy mindset, with the ability to quickly build imperfect solutions and improve them over time
  • Between 3-10 years of relevant industry experience
  • Excitement about shaping the future of photography

Handy to have, but not required:

  • Masters degree or PhD
  • Experience running ML efficiently on-device
  • AWS or Azure certifications
  • A keen interest in photography

Additional benefits:

  • 1 month paid parental leave in addition to government leave, 30 hours a week for 6 months on full pay following return from parental leave (for all parents)
  • Extended sick leave to support our team to get through the many things life can throw our way

Location: Based in our office on Karangahape Road in Auckland, New Zealand; with some days of the week optionally remote. We are also supportive of fully remote members in New Zealand.

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