Machine Learning Engineer

We are Kilter, and we’re on a mission to transform sustainable agriculture and food production by harnessing the power of technology. As the global population grows and diets shift towards plant-based foods, we need innovative ways to grow more food on less land while protecting nature and the environment.

Kilter develops technology to address major challenges for farmers in a sustainable way. Our fully automated agricultural robot, Kilter AX-1, represents a paradigm shift in weed control. Using advanced AI and patented nozzle technology, AX-1 precisely targets weeds without harming crops or soil. This reduces herbicide use by up to 95% and increases crop yield by up to 35%.

About the role

We are looking for a Machine Learning Engineer to help develop the intelligence behind our agricultural robotics technology. You will work across machine learning, computer vision and software engineering to help AX-1 perceive and act in complex, real-world farm environments. From exploring data and training models to deploying and evaluating them on the robot, you will contribute hands-on throughout the development process.

What will you do as a Machine Learning Engineer at Kilter?

• Develop, train and evaluate machine learning and computer vision models for agricultural applications, including weed and crop detection

• Work with image and sensor data collected in real-world field conditions, helping to build reliable datasets and data pipelines

• Improve model performance, robustness and efficiency across varying crops, lighting, weather and operating conditions

• Deploy and integrate models into production software running on robotic systems

• Collaborate with robotics, software and product colleagues to turn customer and field needs into practical technical solutions

• Design experiments, define evaluation metrics and communicate findings to inform development priorities

• Monitor model performance and contribute to ongoing testing, debugging and improvement in the field

• Help establish good engineering practices for machine learning development, testing, versioning and deployment

This role is for you if:

• You have professional experience developing and deploying machine learning models

• You have strong Python skills and experience with machine learning frameworks such as PyTorch or TensorFlow

• You understand computer vision concepts and have worked with image data and model evaluation

• You are comfortable taking work from an initial problem through experimentation, implementation and production deployment

• You care about writing maintainable, well-tested code and building solutions that work reliably outside the lab

• You communicate clearly and enjoy working closely with colleagues across different technical disciplines

• You are curious, practical and comfortable adapting as priorities evolve in a growing company

• You communicate clearly in English

Nice to have

• Experience with robotics, autonomous systems or deploying machine learning on edge devices

• Experience with object detection, image segmentation or other computer vision applications

• Knowledge of MLOps, data versioning, model monitoring or automated machine learning pipelines

• Experience working with agricultural, outdoor or otherwise variable real-world data

• Familiarity with C++, Linux, ROS or cloud infrastructure

Why should you choose Kilter?

• Work on machine learning technology with a direct impact on sustainable food production

• Help build and improve a real-world robotic product, from model development to field testing

• Take ownership and see how your work contributes to a growing technology company

• Collaborate with an engaged, multidisciplinary team in a flat and open environment

• Room to grow as Kilter expands, alongside a competitive salary and an options programme

At Kilter, you will be part of an innovative and rapidly growing startup with global ambitions. You’ll work in an inclusive environment with talented colleagues from a wide range of backgrounds, all sharing a passion for solutions that promote sustainable food production.

We give our people the opportunity to grow and take ownership of their work. Our headquarters are in Langhus, Nordre Follo, with parking and charging facilities for electric cars. We offer a competitive salary and the opportunity to participate in the company’s options programme.

If you are excited by applying machine learning to real-world challenges, enjoy collaborating with technical and creative colleagues, and want to help build technology for more sustainable agriculture, we would like to hear from you.