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Introduction to the position
z.systems is a fast-growing VC backed tech company revolutionizing traditional retail across Africa with a full-stack B2B2C digital ecosystem. They're transforming independent grocery stores into a digitally connected, owner-operated network. We are searching for a talented Machine Learning Engineer who is eager to be part of our mission of modernizing the retail experience. This role is crucial now as we continue to scale our innovative solutions and impact across the continent.
Your role
We are seeking a computer vision specialist Or a smart and adaptable machine Learning Engineer who is willing to focus on computer vision. Your role will involve:
• Leading a small CV/ML engineering team and build the roadmap for detection and recognition models.
• Designing and optimize training pipelines for YOLO-based models (real + synthetic datasets).
• Implement best practices for data collection, augmentation, annotation quality, and tiling for small objects.
• Exploring and evaluate approaches such as OBB vs. HBB, DINOv3 backbones, and multi-GPU distributed training.
• Establishing CI/CD workflows for model training, versioning, deployment, and A/B testing.
• Mentoring junior engineers and promote strong ML engineering culture.
• Collaborating with product and operations teams to deploy models into retailer-facing applications.
Your team
You will be joining a dynamic and fast-paced team of tech enthusiasts at z.systems. Our team is small but highly collaborative, working closely with product and operations to deliver impactful solutions. You'll report to the CTO and collaborate with other engineers in a supportive and innovative environment.
Your qualifications
Required qualifications:
• 4+ years of experience in ML engineering
• Strong problem-solving skills and adaptability
• Proficiency in Python and ML frameworks
• Experience in deploying ML models in production environments
• Excellent communication skills
Nice to have:
• Background in computer vision
• Experience with PyTorch, Ultralytics YOLO, and distributed training on AWS
• Experience with synthetic data generation and annotation pipelines.
• Experience with object detection on small objects, data imbalance, and augmentation strategies.
• Experience with DINO/DINOv2/v3, ViT-based backbones.
• Background in retail tech, OCR, or dense shelf detection.
• On-device optimization experience (TensorRT, TFLite, etc.).
• Knowledge of retail tech applications
Benefits
• Opportunity to make a meaningful impact in African retail
• Collaborative and innovative team culture
• Growth and learning opportunities across diverse tech stacks
• Potential for long-term career advancement within the company
Recruitment process
- CV pre-screening
- AI Interview
- Technical and culture fit interviews with z.systems' team
