Machine Learning Ops Engineer at Careers at Eucalyptus

Eucalyptus is seeking a Machine Learning Ops Engineer to operationalize AI and machine learning models, integrating them into their mission to deliver personalized, data-driven healthcare. The MLOps Engineer will collaborate with Data Science, Engineering, Product and Analytics teams on projects to provide real-time, personalised patient products and AI-driven decision support. The role involves shaping the future of preventive and personalized care, empowering clinicians, coaches, and patients.

Responsibilities will include:

• Pipeline Development and Automation: Design, build, and maintain scalable pipelines for deploying machine learning models using tools like Google Cloud’s Vertex AI, BigQuery and DBT.
• Versioning: Utilize tools like VertexAI or MLflow to ensure proper versioning of data and models, supporting reproducibility and traceability in the ML lifecycle.
• Model Deployment: Develop and manage robust CI/CD pipelines with GitHub Actions for seamless model deployment and updates, ensuring efficient and reliable production rollouts.
• Model Tracking and Monitoring: Use tools such as MLflow or Vertex AI’s built-in tracking features to monitor and manage model performance, handling metrics logging, and model / parameter experimentation.
• Monitoring and Alerting: Set up monitoring systems with Datadog to track model performance, latency, and reliability in real-time, ensuring proactive issue resolution.
• Collaboration and Support: Work closely with data scientists, data engineers, and platform engineering teams to optimise and scale AI solutions, ensuring they align with business objectives and technical best practices.

The ideal candidate will have:

• 4+ years of experience in MLOps, machine learning engineering, or a related field, with a proven track record of deploying and maintaining ML models in production.
• Expertise in cloud services, particularly Google Cloud (Vertex AI, BigQuery), and MLOps tooling.
• Deep understanding of the MLOps lifecycle, from model development and deployment to monitoring and improvement.
• Strong interpersonal skills to collaborate effectively with the data team, engineers, legal and other stakeholders.
• Thrives in ambiguous environments, owning decisions that balance the trade-off between short-term agility and long-term scalability.
• Passionate about transforming healthcare and contributing to impactful patient outcomes through AI and machine learning.

Eucalyptus offers:

• An annual professional development budget, mentors and buddies to level up career.
• Equity to ensure that you are able to benefit in the upside of your contribution in helping Euc grow.
• Range of leave offerings to support you when needed, this includes: personal health and professional development leave, a generous parental leave that offers 20 weeks paid leave for a primary carer, additional miscarriage leave, as well as our Employee Assistance Programme