Machine Learning Engineer
Supermoon Capital
Machine Learning Engineer
We're building AI-driven solutions that harness both mind and body data to provide highly personalised health and wellness experiences. Our technology enables individuals to better understand and improve their mental and physical wellbeing, while also enabling healthcare providers and organisations to deliver more effective and personalised care. Sahha's goal is to revolutionise the health industry by improving user retention, enhancing customer lifetime value, and bolstering individual health outcomes. Sahha is: A simple, and beautiful API that can integrate into any application Curated data insights tailored for the insurance, well-being, fitness, and pharmaceutical industries A new way to build personalised healthcare experiences A powerful set of machine learning models built to understand you, and your health, dynamically. A system that brings together data across wearables
Working at Sahha
We are a fast-growing team of passionate, humble, brilliant, and diverse people, with collective experience in tech, health, neuroscience, b2b, and building successful companies. Every person at Sahha raises the bar—and we're so excited for you to continue that tradition. We're remote-first—you can work from anywhere — but we believe our best work is done in person. We aim to meet up regularly to align ourselves and our work. We strive to be clear in our communication and over-communicate by default. We're early, so you'll have an opportunity to shape not just our product, but the company itself; who we work with, and how we work together.
The Role
Responsibility
As a machine learning engineer you will: Build and maintain CI/CD pipelines for automated testing and deployment of machine learning models developed by the research team. Continuously monitor, evaluate, and report on the performance of deployed models. Implement continuous retraining strategies to adapt to data drift. Optimise and scale inference pipeline to efficiently handle high volumes of requests.
Qualifications
Strong background in computer science, statistics, neural networks, and pattern recognition Proficient in creating and testing algorithms Experience with scikit-learn or PyTorch Good analytical and problem-solving skills Excellent organizational and communication skills Capacity to work independently and in a team environment Bachelor's or Master's degree in Computer Science, Mathematics, or a related field
Preferred but not required
background in insurance, wellbeing, healthcare industries background in any of the following fields: behavioural science, cognitive science, neuroscience, wearables, ubiquitous computing, biomedical engineering
$157.5k
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