Machine Learning Engineer

Company Overview

Circadia Health is a medical device and data technology company that has developed the worlds 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. Were 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 Overview

As 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 and performance, 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:

1. 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.
2. 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.
3. 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 or 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.

J-18808-Ljbffr