Machine Learning Scientist

At mDoc, we are revolutionizing health care in low
- and middle-income communities by leveraging AI-driven virtual self-care health coaching, innovative solutions for health literacy, and tools for medication adherence and personalized support. Our mission is to provide holistic care and improve outcomes for individuals managing chronic health conditions and regular health needs. Join our team to be a part of this transformative journey.

**Role Overview**
The Machine Learning Scientist will develop and implement ML models to enhance telehealth services, requiring a deep understanding of algorithms, healthcare data, and a passion for improving patient outcomes through innovative technology. This role is ideal for those who enjoy exploring profound ML research questions, excel with ambitious objectives, and are motivated to deploy general AI systems for a sustainable world.

**Key Responsibilities**
- Propel the performance of our large language models (LLMs) tailored for virtual health coaching through cutting-edge research and development initiatives.
- Lead the full end-to-end machine learning development process, including data ingestion and preparation, feature engineering, analysis and modelling, model deployment, performance tracking, and documentation.
- Develop evaluation processes to ensure accuracy, fairness, reproducibility, and scalability of ML models.
- Conduct research in ML and AI, focusing on large language models, to identify opportunities for innovation and product improvement.
- Perform literature reviews and share summaries of the latest research with the team to stay informed about the latest developments and trends.
- Implement prototypes of promising new solutions to explore opportunities, test feasibility, and assess practicality, ensuring ML engineers focus on viable solutions.
- Collaborate with cross-functional teams, including product managers, engineers, data scientists, and health professionals, to develop and implement ML solutions that meet business objectives.
- Develop and maintain technical reports, research papers, and presentations to communicate research findings and results to both technical and non-technical stakeholders.

**Required Skills & Qualifications**
- Minimum of Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Biomedical Engineering or a related field.
- Proven experience (5+ years) in developing and deploying machine learning models in a professional setting, preferably in healthcare.Programming languages: Python,ML frameworks and libraries: TensorFlow, PyTorch, or Scikit-Learn, Cloud platforms: GCP, AWS, or Azure
- Solid understanding of statistical methods, data analysis, and data visualization techniques.
- Experience with healthcare data, including electronic health records (EHR), medical imaging, or genomic data is a plus.
- Excellent research and analytical skills, with the ability to conduct literature reviews and implement prototypes of new solutions
- Strong communication and presentation skills, with the ability to write technical reports, research papers, and present findings to both technical and non-technical stakeholders
- Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines
- Strong focus on large language models, with experience in researching and implementing solutions using these models
- Strong technical skills in ML, including experience with:
**Preferred Skills**
- Experience in the healthcare domain or with digital health platforms.
- Hands-on experience with NLP techniques and tools like SpaCy, Hugging Face, or OpenAI APIs.
- Strong understanding of data privacy, security, and compliance standards in healthcare (e.g., HIPAA).
- Have a Ph.D. degree in Computer Science or related technical field (Based on budget) - can be excluded
- Have published research in the domain of LLMs or strong publication record in top-tier ML journals
- Are deeply motivated by the potential to improve healthcare by capitalising on the advances of LLMs.

**Why Join mDoc?**
- Be part of a mission-driven team transforming healthcare in underserved communities.
- Opportunity to work on cutting-edge AI solutions in a rapidly growing health tech space.
- Competitive compensation and opportunities for professional growth.
- Flexible working environment with a focus on innovation and impact.

Pay: E£50,000.00 - E£75,000.00 per month

Application Question(s):

- You are tasked with building a predictive model to identify patients at high risk of developing chronic diseases based on their medical history, demographics, and lifestyle factors.

How would you approach feature selection and engineering for this problem?
What machine learning algorithms would you consider, and how would you decide which one to use?
What strategies would you implement to optimize model performance while preventing overfitting?
- You are developing an AI-powered diagnostic