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Machine Learning Engineer

Job Description

Company OverviewCircadia Health is a medical device and data technology company that has developed the world's first FDA cleared contactless remote patient monitoring system. Powered by cutting-edge technology and AI, the system allows for the early detection of medical events such as Congestive Heart Failure, COPD Exacerbations, Pneumonia, Sepsis, UTIs, and Falls. We're monitoring over 28,000+ lives daily and growing rapidly. As we scale our team, Circadia is looking for energetic, personable, and solutions-oriented individuals driven by creating the ultimate customer experience. Prior experience in healthcare is a big plus, but not required. Our mission is to enhance patient outcomes and improve healthcare processes by providing cutting-edge solutions to healthcare providers and patients alike.
Position OverviewAs a Machine Learning Engineer, you will design, build, and maintain end-to-end machine learning pipelines, transforming experimental models into scalable, production-ready systems while closely collaborating with the Product Design and Engineering (PDE) team to create impactful ML-driven products in the healthcare setting. In addition to optimizing infrastructure, automating workflows, and ensuring seamless integration from model development to deployment, you will play a key role in building and iterating on the actual products that leverage machine learning to deliver value to patients and healthcare professionals. With a strong focus on scalability, performance and you will help bridge the gap between cutting-edge algorithms and real-world applications in a fast-paced, startup environment - driving our mission of saving lives.

Key Responsibilities:

  • Ownership of Machine Learning Infrastructure:
  • Develop, deploy, and maintain scalable pipelines for both Circadia’s proprietary ML models and off-the-shelf solutions.
  • Optimize model training and inference workflows to handle large-scale, real-time data efficiently.
  • Design robust model monitoring systems to track performance, detect drift, and ensure reliability.
  • Implement infrastructure to support the experimentation and productionization of ML models cost-effectively in AWS and Snowflake.

  • Building and Deploying ML-Driven Products:
  • Collaborate closely with the Product Design and Engineering (PDE) team to design, build, and iterate on ML-powered products.
  • Translate complex machine learning algorithms into user-facing features and services.
  • Work with key stakeholders to ensure alignment between technical implementation and product goals.
  • Define and develop APIs for seamless integration of ML models with product functionalities.

  • Orchestration of Scalable ML Pipelines:
  • Engage with data and ML scientists to plan the architecture for end-to-end machine learning workflows.
  • Implement scalable training and deployment pipelines using tools such as Apache Airflow and Kubernetes.
  • Perform comprehensive testing to ensure reliability and accuracy of deployed models.
  • Develop instrumentation and automated alerts to manage system health and detect issues in real-time.

Attributes:

  • Technical acumen: Mastery of computer science fundamentals and understanding of core machine learning concepts. 
  • Detail oriented: Responsible for mission-critical healthcare machine learning models. 
  • Communications and Trust: Good communication skills with the ability to liaise with both technical and non-technical stakeholders.
  • Organization and Getting Stuff Done: Juggling multiple projects and timelines. Prioritizing. Keen eye for detail in all tasks and projects.
  • Growth Mindset: Your ability to learn from mistakes, reflect on mistakes, and not make mistakes again. Being curious and asking questions and showing resilience in the face of setbacks. 

Benefits:

  • Join an energetic, diverse team dedicated to working towards the challenge of improving and saving patient lives
  • Private health insurance with Vitality Health for you and your family, including discounted gym memberships, wellness retreats, fitness devices, and lots more
  • 28 days paid annual leave during each holiday year (including bank holidays)
  • Fully financed learning and personal development courses to help you grow in your role
  • Opportunity to attend conferences and acquire certifications, paid for by the company
  • New laptop of your choice for you to work on either at home, our at Circadia’s London Bridge office
  • Flexible / hybrid working to suit your personal circumstances and allow you to be productive wherever you are most comfortable working
  • Participate in and help plan regular team events, lunches and dinners

Location

London

Job Overview
Job Posted:
3 days ago
Job Type
Full Time

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