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Machine Learning Engineer

Circadia Health
Full-time
On-site
London, United Kingdom
Technology
Company Overview

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, 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
Apply now
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