Machine Learning Engineer - Hybrid Remote

About Vita Health Vita Health is a dynamic startup in the health, nutrition, and fitness industry. Our innovative product has positively affected the lives of over 130,000 people in our core market, and we are now eager to expand our expertise and reach globally.

Our mission is to enhance our presence not just in the B2C sector, where we began, but also in B2B by integrating into corporate welfare programs for both large enterprises and SMEs that shape our market. By utilising AI and algorithms, we create personalised diet and training plans tailored to user inputs during onboarding, which adapt continuously to reflect their progress. Our dedicated team of nutritionists and personal trainers is committed to guiding users throughout their journey to help them reach their goals.

We’re hiring our first Machine Learning Engineer to spearhead a new strategic initiative aimed at modelling individual health progress and behaviour in a more intelligent, personalised, and explainable way.

This role is a rare opportunity to lay the technical and strategic foundation for how we assess and support our users’ wellness journeys through data. You’ll work at the intersection of health science, behavioural modelling, and machine learning, bringing innovative ideas to life, backed by real-world impact.

Design and implement the core ML systems behind a new health intelligence initiative, balancing rule-based and ML-based approaches.

Translate complex user behaviours (nutrition, training, physical activity, sleep, engagement, etc) into actionable, data-driven insights.

Own the entire ML lifecycle : from data exploration and feature engineering to model deployment and monitoring.

Build data-ingestion flows and automated training jobs on AWS

Work closely with cross-functional stakeholders, including Product, Engineering, Design, and Health Experts, to define meaningful signals and feedback loops.

Help define the long-term ML roadmap—including opportunities in personalisation, recommendations, and behavioural nudging.

5+ years of experience in applied machine learning, with strong foundations in algorithm design and data pipelines.

Vision to architect and evolve our entire ML tech stack—from experimentation frameworks and data pipelines to deployment and MLOps infrastructure.

Experience building and deploying ML solutions in production environments.

Ability to independently own projects from data exploration to delivery.

Assessment Review : We’ll discuss your test results to understand your thought process.

Cultural Fit Interview : Ensure your values align with our company culture to help everyone thrive.