Machine Learning Engineer - All levels
HalterAucklandPosted 26 March 2026
Job Description
Machine Learning Engineer - All levels
ABOUT HALTER
At Halter, we’re on a mission to enable farmers and graziers to run the most productive and sustainable operations. Our customers are using Halter to break free from the time-intensive constraints of conventional practices. Imagine watching 500 cattle stand up and walk calmly towards their next break? No quad bikes, no dogs, no fences. Just a group of cattle walking at their own pace. People say it looks like magic. Our customers are revolutionizing grazing with Halter. It's changing lives and transforming an industry. People join Halter to do meaningful work. By joining us you’ll be solving challenging problems within a talented team and a culture built for high performance. Our team out-think, out-work and out-care. We’re committed to delivering real change in the world - this isn’t easy, and in truth, we love that it’s hard.
We’re backed to deliver on a mission that matters by Tier 1 investors including Founders Fund https://foundersfund.com, Bessemer Venture Partners https://www.bvp.com/, BOND, https://www.bondcap.com/ DCVC https://www.dcvc.com/, Blackbird https://www.blackbird.vc/, Promus Ventures https://www.promusventures.com/, Rocket Lab’s Peter Beck and Icehouse ventures https://www.icehouseventures.co.nz/?utm_term=icehouse%20ventures&utm_campaign=Brand+Keywords&utm_source=adwords&utm_medium=ppc&hsa_acc=4064636360&hsa_cam=16902737884&hsa_grp=134004309485&hsa_ad=592971340272&hsa_src=g&hsa_tgt=kwd-1082530126230&hsa_kw=icehouse%20ventures&hsa_mt=b&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQjw2v-gBhC1ARIsAOQdKY0J0DepRVFDmjQlAkJPbZuQnLSA5UVzUzOXYiPxkjX-SeVa513_BhkaAr-MEALw_wcB.
To find out more, visit our LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/.
ABOUT THE ROLE
Halter’s Predictive Systems group is dedicated to the development of advanced models to provider farmers with the most accurate insight to optimise their operations. To provide farmers with the highest quality insights, we’re building upon the bleeding edge of scientific advancements with unmatched access to rich, novel data to develop a cutting edge agricultural modelling system.
You’ll play a pivotal role in one of the machine learning teams within the group, where you could be building advanced models of pasture growth and land properties that power intelligent, modelling animal state, health and activity, and much more. Applications could range from remote sensing of pasture biomass, identification of animal heat events, to grazing interval simulation for advanced recommendations.
You will be owning end to end development of machine learning pipelines, advanced contemporary modelling, to deployment and monitoring. You will work with great team-mates in engineering, product and design to achieve outsized results. The impact of our work is profound, and we take that responsibility seriously. As a member of the group, you'll share our passion for technology and our commitment to optimizing the management of pastural grazing systems.
You will be responsible for
- 🌱Modeling, from biological processes to farm operations: You will drive development of predictive systems to solve real-world challenges faced by farmers.
- 📚Research, from technical to agriculture: you will be required to conduct extensive literature reviews, and stay ahead of the curve with respect to both machine-learning systems, and pasture science.
- 🛠️Model development: design, dataset construction, training and optimization: Rarely do we utilize a model off the shelf. You will own the architectural design, and all phases of model development.
- 👀Supporting your work in production: Halter engineers demonstrate a high level of ownership. We support what we build, and we learn from our systems behavior in the field.
- 🧠Proactive innovation: As a member of the data discipline it is expected that you will exercise a high degree of creativity to proactively deliver innovati ... (truncated, view full listing at source)
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