This role is for an engineer who can contribute meaningfully from day one, working on challenging projects in an agricultural environment alongside experts in the field.
About the Role
A Computer Vision/Machine Learning Engineer is required to work on complex, real-world problems where off-the-shelf solutions are rarely sufficient. Projects typically begin with an intensive research phase, focused on understanding the problem space, evaluating approaches, and developing practical, scalable solutions.
You will work closely with subject-matter experts, share knowledge within the team, and provide technical direction where appropriate. This role suits someone who thrives on difficult problems, complex questions, and applied research with real impact.
What Youll Do
Design, develop, and deploy computer vision and machine learning solutions for real-world agricultural use cases
Lead and contribute to early-stage research phases to define viable technical approaches
Translate complex problems into practical ML and CV solutions
Collaborate with experts in the field and share knowledge across the team
Provide technical guidance and direction based on experience and expertise
Engage with clients and visit sites as required to understand real-world constraints and data
Contribute value immediately through hands-on development and problem-solving
Minimum Requirements
MSc or MEng in Machine Learning, Computer Vision, or a closely related field
OR
BEng or BSc with strong, relevant industry experience in machine learning or computer vision
Strong theoretical and practical understanding of machine learning and computer vision
Ability to work independently and take ownership of complex technical challenges
Comfortable working remotely with periodic travel
Strong communication skills and the ability to explain technical concepts clearly
Academic & Performance Expectations
A strong academic record and clear evidence of exceptional technical ability
Proven ability to add value quickly in complex or demanding projects
High standards for problem-solving, code quality, and technical rigour
Additional Experience (Advantageous)
Experience applying ML or CV in real-world, non-lab environments
Exposure to agricultural, industrial, or field-based systems
Research-heavy project experience or applied R&D background
Experience working with incomplete, noisy, or real-world data
Ability to bridge research and production-focused implementation
Working Environment & Travel
Remote role, based in South Africa
Travel to client sites as required
All travel-related expenses are covered
Only shortlisted candidates will be contacted. If you do not receive feedback within a reasonable period, please consider your application unsuccessful.
