🚀 About us
Aisthesis Medical is a medical technology startup operating at the forefront of digital healthcare. We combine clinical patient data with state-of-the-art machine learning algorithms to predict risks and complications across the patient journey. Our flagship product, VIOSync, is an AI-driven decision-support platform that empowers hospitals to deliver timely, personalised interventions—from admission to discharge.
We are looking for a talented Junior to Mid-Level Machine Learning Engineer to join our growing team at Aisthesis Medical. This is an exciting opportunity to contribute to the development of predictive models and real-world applications that impact patient outcomes. You will work closely with senior team members and play a hands-on role in cleaning and analyzing clinical datasets, developing and evaluating ML models, and supporting the data pipeline for our AI product.
🎯 Responsibilities
- Develop and deploy deep machine learning models for predictive analytics in acute care, under the guidance of the AI Lead.
- Collaborate with the AI team to design robust, scalable ML pipelines and data processing workflows.
- Contribute to the continuous improvement of model performance, reproducibility, and robustness with SOTA techniques.
- Work with software engineers to integrate AI models into production systems.
- Participate in model evaluation, monitoring, tuning, and compliance with healthcare data privacy standards.
- Stay up-to-date with emerging technologies and propose improvements for existing AI/ML solutions.
👀 What we’re looking for
- Solid Python skills — you write clean, modular and testable code without needing to be reminded.
- Deep enough understanding of the theory to steer it in practice. Everyone uses AI to write code these days; far fewer can critically evaluate what it produces, catch the wrong tradeoffs, and push it in the right direction.
- A team-first mindset — you bring your own ideas to the table while staying aligned with the team’s priorities and being a good collaborator.
- Sharp instincts for model performance and data quality — you notice when numbers don’t make sense, can explain what the metrics actually mean, and know what to try next.
📋 Minimum Qualifications
We are looking for professionals with the following skills and experience:
- BSc/MSc in Computer Science, Electrical & Computer Engineering, Biomedical Engineering, or related field with a focus on AI/ML.
- 1–3 years of experience in a data science role (or strong academic projects/internships).
- Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Good understanding of the machine learning lifecycle (data preparation, model development, validation, deployment).
- Strong analytical and communication skills; detail-oriented and proactive.
- Ability to work independently in a remote, fast-paced startup environment.
- Fluent in English with excellent communication and teamwork skills.
💡 Nice-to-Haves
If you have the following, it’s a strong plus:
- Exposure to working in healthcare/biomedical settings with real-world data.
- Experience training deep models in practice — knowing the tricks and pitfalls that don’t show up in tutorials.
- Strong coding practices and collaborative mindset.
- Startup experience or interest in working in a high-growth environment.
🏢 Team Culture
- We treat each other with respect, humility, and openness;
- We value curiosity, experimentation, and fast learning;
- We embrace flexibility and focus on solving real-world problems that matter;
- We believe in diversity—of background, perspective, and skill set;
- We value open dialogue and brainstorming across multidisciplinary teams;
- We prioritize deep work, async collaboration, and only meet when it matters;
- Work from anywhere in the world (within ±3h of GMT), as long as the WiFi’s solid.
🎁 What We Offer
- Competitive salary tailored to your experience and skills;
- Fully remote work with flexible hours and trust-based autonomy;
- 25 days holiday, plus bank holidays;
- A mission-driven, close-knit team working on meaningful problems;
- Opportunities for personal growth through conferences, events, and mentorship.