Machine Learning Engineer

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 health sector, where we began, but also in corporate wellness by integrating into corporate programs for both large enterprises and SMEs that shape our market. We strive to make individuals more conscious of the benefits of a healthy lifestyle, demonstrating that dieting and exercising can seamlessly fit into their daily routines rather than being a chore.

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. If you're passionate about transforming lives, join Vita Health!

About The Role

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.

Your responsibilities will include:

1. Design and implement the core ML systems behind a new health intelligence initiative, balancing rule-based and ML-based approaches.
2. Translate complex user behaviours (nutrition, training, physical activity, sleep, engagement, etc.) into actionable, data-driven insights.
3. Own the entire ML lifecycle: from data exploration and feature engineering to model deployment and monitoring.
4. Build data-ingestion flows and automated training jobs on AWS.
5. Work closely with cross-functional stakeholders, including Product, Engineering, Design, and Health Experts, to define meaningful signals and feedback loops.
6. Ensure a high level of transparency and explainability so our users can understand and trust the results.
7. Help define the long-term ML roadmap—including opportunities in personalisation, recommendations, and behavioural nudging.

What You’ll Bring

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. Passion for simplifying complex concepts for end users. Ability to independently own projects from data exploration to delivery. Experience working closely with product and domain experts to define and refine model objectives.

Bonus Points For

• Domain experience in health, fitness, or behavioural science
• Experience with consumer-facing product integrations
• Experience in a startup or fast-paced product environment

Based on experience, we offer:

• Autonomy and flexibility: work from wherever you want, with the option to visit our modern Milan office.
• Personalised learning budget with dedicated learning time weekly.
• A dynamic work environment where your ideas influence our strategies and product development.
• Leadership committed to your career progression.
• A unique opportunity to create a significant impact in the health sector.

Recruiting Process

1. Asynchronous Assessment: Evaluate reasoning abilities, logical and critical thinking, and behaviour in challenging situations.
2. Assessment Review: Discuss your test results to understand your thought process.
3. Technical Evaluation: Tailored technical assessment for the role.
4. Technical Review: Discuss your approach and reasoning behind your solutions.
5. Cultural Fit Interview: Ensure your values align with our company culture.