Computer Vision/Machine Learning Engineer

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