AI/ML ENGINEER
Role details
Job location
Tech stack
Job description
This is a high-impact role for an AI/ML Engineer passionate about building real-world applications. You will develop the core intelligence behind ZenroxIQcomputer vision models for equipment identification, AI-driven pricing engines, predictive procurement algorithms, and automated compliance intelligence. Your work will directly influence how healthcare organisations source, manage, and purchase medical equipment.
- Develop and optimise visual equipment search models using computer vision, image recognition, and specification extraction.
- Build price optimisation algorithms for real-time benchmarking across suppliers and markets.
- Design and deploy predictive procurement models (6090 day demand forecasting).
- Implement supplier matching algorithms with performance scoring and ranking logic.
- Integrate and orchestrate third-party AI services (OpenAI, Google Cloud Vision, etc.).
- Establish end-to-end model lifecycle processes including monitoring, evaluation, and continuous improvement.
- Work with diverse datasets including supplier catalogues, equipment images, pricing data, and transaction history.
- Collaborate with engineering and product teams to deploy production-grade ML systems., * Work across diverse AI domains: computer vision, pricing, forecasting, matching systems.
- See direct, measurable impact of your work (cost reduction, speed, accuracy improvements).
- Shape Zenroxs AI strategy as a founding ML Engineer.
- Access to rich, structured and unstructured healthcare procurement datasets.
- Earn meaningful equity in a rapidly growing healthtech startup.
Requirements
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3+ years hands-on experience developing and deploying machine learning systems.
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Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, scikit-learn.
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Experience with computer vision, image recognition, or object detection.
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Practical background in recommendation systems, ranking models, or matching algorithms.
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Strong understanding of time-series forecasting and predictive analytics.
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Ability to deploy, scale, and monitor machine learning models in production environments.
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Excellent communication skills for explaining technical concepts to non-technical stakeholders.
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Experience working on marketplace, e-commerce, or pricing optimisation systems.
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Familiarity with NLP techniques for document or specification extraction.
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Background in healthcare analytics, supply chain, or procurement systems.
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Experience integrating commercial AI APIs (OpenAI, Google Cloud Vision, etc.).
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Knowledge of A/B testing, experimentation frameworks, and model experimentation pipelines.