Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and implement algorithms for physiological monitoring and alert systems.
- Company: Join Biostream, a leader in health tech innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact on health monitoring with cutting-edge AI technology.
- Qualifications: MSc or PhD in relevant fields and strong Python programming skills.
- Other info: Collaborative environment with a focus on real-world applications.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for an AI scientist or machine learning engineer to design and implement the algorithms that power Biostream’s physiological monitoring and alert systems. You will work closely with the biostatistics team to translate probabilistic and Bayesian models into deployable algorithms that operate on real‑world sensor data. The role focuses on building robust machine learning systems capable of detecting physiological deterioration from multi‑sensor inputs in complex and noisy environments. You will collaborate with engineers, statisticians, and medical advisors to develop models that can operate on‑device or in distributed systems with constrained connectivity.
Responsibilities
- Design and develop machine learning algorithms for physiological signal analysis and risk detection.
- Work closely with the biostatistician to implement Bayesian models and probabilistic frameworks.
- Develop models combining vital signs, motion data, and contextual signals.
- Build pipelines for sensor data processing, feature extraction, and model training.
- Implement algorithms suitable for real‑time and edge deployment.
- Evaluate model performance and robustness across heterogeneous datasets.
- Develop simulation and testing environments for algorithm validation.
- Contribute to the integration of models into the broader software platform.
Profile
- MSc or PhD in machine learning, artificial intelligence, computer science, applied mathematics, or a related field.
- Strong experience developing machine learning models for time‑series or sensor data.
- Strong programming skills in Python.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience building data pipelines and training workflows.
- Ability to work with imperfect, noisy, or incomplete datasets.
Nice to Have
- Experience with physiological signal processing (ECG, PPG, respiration, etc.).
- Experience working with wearables or biosensor data.
- Familiarity with Bayesian modelling or probabilistic machine learning.
- Experience deploying models on edge devices or constrained hardware.
- Experience with healthtech, medical AI, or clinical datasets.
What You Will Work On
- Physiological signal processing.
- Integration of probabilistic models with machine learning systems.
- Real‑time monitoring and alert systems.
- Deployment of models in constrained operational environments.
Company Biostream
Experience Senior (5+ years of experience)
AI Scientist / Machine Learning Engineer in London employer: NLP PEOPLE
Contact Detail:
NLP PEOPLE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Scientist / Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and machine learning space on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning algorithms or physiological signal processing. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python and machine learning frameworks like PyTorch or TensorFlow.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AI Scientist / Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and AI, especially in relation to physiological data. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background makes you a perfect fit for our team. We love seeing enthusiasm and a clear understanding of what we do at Biostream.
Showcase Your Technical Skills: Don’t forget to mention your programming prowess, especially in Python and any machine learning frameworks like PyTorch or TensorFlow. We’re keen on candidates who can hit the ground running, so highlight any relevant technical projects you've worked on.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Biostream!
How to prepare for a job interview at NLP PEOPLE
✨Know Your Algorithms
Make sure you brush up on the algorithms relevant to physiological signal analysis and risk detection. Be ready to discuss how you would implement Bayesian models and probabilistic frameworks in real-world scenarios, as this will show your understanding of the role's core responsibilities.
✨Showcase Your Programming Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your previous projects. Have examples ready that highlight your experience with machine learning frameworks like PyTorch or TensorFlow.
✨Discuss Real-World Applications
Be prepared to talk about how you've dealt with noisy or incomplete datasets in the past. Discuss specific challenges you've faced and how you overcame them, especially in the context of time-series or sensor data. This will help illustrate your practical experience and problem-solving skills.
✨Collaborative Mindset
Since the role involves working closely with engineers, statisticians, and medical advisors, emphasise your teamwork skills. Share examples of successful collaborations and how you’ve integrated feedback from different disciplines to improve your models or algorithms.