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- Tasks: Design and develop machine learning models to transform cancer care using real-world patient data.
- Company: Stealth-stage MedTech company revolutionising oncology with advanced AI.
- Benefits: Flexible contract with potential for full-time, access to high-quality datasets, and collaboration with experts.
- Why this job: Make a real impact in healthcare by applying AI to critical cancer challenges.
- Qualifications: Strong ML background, experience with healthcare data, and programming skills in Python.
- Other info: Join a fast-paced environment and help shape a high-growth company pre-public launch.
The predicted salary is between 60000 - 80000 £ per year.
Location: Remote (Contract)
Duration: 3–6 month contract (with potential to convert to full-time)
Company: Stealth-stage MedTech (AI in Oncology)
About the Company
Our client is rapidly scaling, stealth-stage medtech company applying advanced AI to transform cancer care. Founded in late 2025 and led by experienced operators and researchers, we are building proprietary, data-driven models to improve cancer surveillance, diagnosis, and treatment decision-making. Our work is powered by rich longitudinal patient datasets, with strong in-house expertise in genomics. We are not focused on traditional imaging AI—instead, we tackle complex, multimodal clinical data to drive real-world impact in oncology.
The Opportunity
We are looking for exceptional AI Researchers / ML Engineers to join us on a high-impact contract basis (3–6 months) to accelerate model development across large-scale patient datasets. You will work closely with our Head of AI and core research team, contributing to the design, development, and deployment of models for:
- Risk prediction
- Patient outcome modeling
- Clinical decision support
High-performing contractors will be considered for full-time roles as we expand our team in Boston later this year.
What You’ll Do
- Design, build, and evaluate machine learning models on large-scale longitudinal patient datasets (e.g., EHR)
- Develop models for risk stratification and outcome prediction in oncology
- Work with multimodal data (clinical, genomic, and other structured/unstructured sources)
- Own the end-to-end ML lifecycle: data processing, experimentation, validation, and deployment
- Collaborate closely with cross-functional teams including AI researchers, engineers, and domain experts
- Translate research insights into production-ready systems
What We’re Looking For
Core Requirements
- Strong background in machine learning and ML engineering
- Experience working with real-world healthcare data, especially:
- Electronic Health Records (EHR)
- Longitudinal patient datasets
Preferred / Differentiators
- Experience with genomics or multimodal biomedical data
- Track record of publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, Nature, Science)
- Experience in healthcare AI, medtech, or clinical data environments
- Background in statistical modeling, causal inference, or time-series analysis
Who You Are
- A hands-on builder who can move quickly from idea → experiment → production
- Comfortable working in a fast-paced, early-stage environment
- Able to balance research depth with engineering execution
- Motivated by applying AI to high-impact problems in healthcare
Why Join Us
- Work on cutting-edge AI problems in cancer care with real-world impact
- Access to proprietary, high-quality patient datasets
- Collaborate with a world-class AI and genomics team
- Flexible contract structure with clear path to full-time
- Join early and help shape a high-growth company pre-public launch
Machine Learning Researcher employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in AI and healthcare. Attend relevant meetups or webinars to connect with potential colleagues and get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to healthcare data. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past projects and how they relate to the role you're applying for, especially in oncology and patient data.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in machine learning and healthcare data. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or publications!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about applying AI in oncology and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your enthusiasm!
Showcase Your Projects: If you've worked on any interesting ML projects, especially those involving healthcare data, make sure to mention them. We’re keen to see your hands-on experience and how you’ve tackled real-world problems in your previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at DeepRec.ai
✨Know Your ML Models Inside Out
Make sure you can discuss your experience with machine learning models in detail. Be prepared to explain the algorithms you've used, how you approached model design, and any challenges you faced during deployment. This will show your depth of knowledge and hands-on experience.
✨Familiarise Yourself with Healthcare Data
Since the role involves working with Electronic Health Records and longitudinal patient datasets, brush up on your understanding of these data types. Be ready to discuss how you've handled real-world healthcare data in the past and any specific projects that relate to oncology or genomics.
✨Prepare for Technical Questions
Expect technical questions that test your programming skills, especially in Python and frameworks like PyTorch or TensorFlow. Practise coding problems and be ready to demonstrate your thought process. This will help you showcase your engineering execution alongside your research capabilities.
✨Show Your Passion for Impactful AI
This company is focused on transforming cancer care, so convey your motivation for applying AI to high-impact problems in healthcare. Share any relevant experiences or projects that highlight your commitment to making a difference in this field, as it will resonate well with the interviewers.