{
  "job_id": "LETlIlAnil_n8q91AAAAAA==",
  "job_city": "London",
  "job_state": null,
  "job_title": "AI Scientist​/Machine Learning Engineer",
  "job_salary": null,
  "job_country": "GB",
  "job_benefits": null,
  "job_latitude": 51.5072178,
  "job_location": "London",
  "job_onet_soc": null,
  "apply_options": [
    {
      "is_direct": false,
      "publisher": "Learn4Good",
      "apply_link": "https://www.learn4good.com/jobs/london/uk/info_technology/4969038564/e/"
    }
  ],
  "employer_logo": null,
  "employer_name": "Biostream",
  "job_is_remote": false,
  "job_longitude": -0.12758619999999998,
  "job_posted_at": "2 days ago",
  "job_publisher": "Learn4Good",
  "job_apply_link": "https://www.learn4good.com/jobs/london/uk/info_technology/4969038564/e/",
  "job_highlights": {},
  "job_max_salary": null,
  "job_min_salary": null,
  "job_description": "Position: AI Scientist / Machine Learning Engineer Location: Greater London AI Scientist / Machine Learning Engineer RoleWe 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.ResponsibilitiesDesign and develop machine learning algorithms for physiological signal analysis and risk detectionWork closely with the biostatistician to implement Bayesian models and probabilistic frameworksDevelop models combining vital signs, motion data, and contextual signalsBuild pipelines for sensor data processing, feature extraction, and model trainingImplement algorithms suitable for real-time and edge deploymentEvaluate model performance and robustness across heterogeneous datasetsDevelop simulation and testing environments for algorithm validationContribute to the integration of models into the broader software platformProfileMSc or PhD in machine learning, artificial intelligence, computer science, applied mathematics, or a related fieldStrong experience developing machine learning models for time-series or sensor dataStrong programming skills in PythonExperience with machine learning frameworks such as PyTorch, Tensor Flow, or JAXExperience building data pipelines and training workflowsAbility to work with imperfect, noisy, or incomplete datasetsNice to HaveExperience with physiological signal processing (ECG, PPG, respiration, etc.)Experience working with wearables or biosensor dataFamiliarity with Bayesian modelling or probabilistic machine learningExperience deploying models on edge devices or constrained hardwareExperience with healthtech, medical AI, or clinical datasetsWhat You Will Work OnPhysiological signal processingIntegration of probabilistic models with machine learning systemsReal-time monitoring and alert systemsDeployment of models in constrained operational environments#J-18808-Ljbffr",
  "job_google_link": "https://www.google.com/search?ibp=htl;jobs&q=machine+learning+engineer+jobs+in+the+last+month&htidocid=LETlIlAnil_n8q91AAAAAA%3D%3D&hl=en-GB&shndl=37&shmd=H4sIAAAAAAAA_xWLMQrCQBAAsU1rZ7W1RU4EG60MiAix8gHhci53K8luuN0iZXpLwQfmJcZmYBim-K6K6nyDRyBkI7V5eru7D4kYoUafmTjChePimGGePvCSFnQpIYEwXEVih5tTMhv06JxqV0Y1bxTKIL0TxlZGt0z6R6PJZxw6b9jsD7uxHDhu1xWJWkbfAzHUwk_hHzVr5G6ZAAAA&shmds=v1_ATWGeeNrZFIFuOI8rGvza-kK3lK5veLFBIrrgkzplecR7e2uXw&source=sh/x/job/li/m1/1#fpstate=tldetail&htivrt=jobs&htiq=machine+learning+engineer+jobs+in+the+last+month&htidocid=LETlIlAnil_n8q91AAAAAA%3D%3D",
  "employer_reviews": null,
  "employer_website": "https://biostream.bio",
  "job_onet_job_zone": null,
  "job_salary_period": null,
  "job_salary_string": null,
  "job_apply_is_direct": false,
  "job_employment_type": "Full–time",
  "job_benefits_strings": null,
  "job_employment_types": [
    "FULLTIME"
  ],
  "job_posted_at_timestamp": 1774483200,
  "job_posted_at_datetime_utc": "2026-03-26T00:00:00.000Z"
}