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- 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 programming skills in Python.
- Other info: Collaborative environment with a focus on real-world applications and career advancement.
The predicted salary is between 50000 - 70000 £ 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
AI Scientist / Machine Learning Engineer in London employer: Biostream
Contact Detail:
Biostream 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. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving time-series or sensor data. This is your chance to demonstrate your expertise and creativity, so make it shine!
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithms and coding skills. Practice common machine learning problems and be ready to discuss your thought process. We want you to feel confident and ready to impress!
✨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 genuinely interested in joining our team at StudySmarter.
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 time-series or sensor data. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about physiological monitoring and how your background makes you a great fit for our team. Let us know what excites you about the role and our mission.
Showcase Your Technical Skills: Be sure to mention your programming skills in Python and any experience with frameworks like PyTorch or TensorFlow. We love seeing candidates who can demonstrate their technical prowess, so include specific examples of your work!
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 shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Biostream
✨Know Your Algorithms
Make sure you brush up on the algorithms relevant to physiological monitoring and Bayesian models. Be ready to discuss how you've implemented these in past projects, especially in noisy environments.
✨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, so practice coding challenges related to machine learning frameworks like PyTorch or TensorFlow.
✨Understand the Data
Familiarise yourself with time-series and sensor data, as well as how to handle imperfect datasets. Be prepared to discuss your experience with data pipelines and feature extraction, as this will be crucial for the role.
✨Collaborate and Communicate
This role involves working closely with engineers and biostatisticians, so highlight your teamwork skills. Prepare examples of how you've successfully collaborated on projects, especially in healthtech or with biosensor data.