Machine Learning Engineer

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