At Health Innovation Labs, we are revolutionising healthcare through cutting-edge technology, delivering innovative solutions that transform how care is accessed, delivered, and managed.
As a dynamic and fast-paced organisation, we thrive at the intersection of healthcare and technology, empowering providers, patients, and organisations to achieve better outcomes through smarter, more efficient systems.
Our team of forward-thinkers is dedicated to solving complex challenges with creativity and precision.
Whether it's streamlining workflows, enabling real-time data insights, or enhancing patient engagement, Health Innovation Labs is at the forefront of reshaping the future of healthcare.
Rooted in innovation and driven by impact, we embrace agility and collaboration as our core strengths.
In a rapidly evolving industry, we remain steadfast in our mission: to advance healthcare systems for a healthier, more connected world.
Join us as we push boundaries and reimagine what's possible in healthcare technology.
About the role: We are seeking a highly skilled Senior Machine Learning Engineer with a strong focus on Machine Learning Operations (MLOps) to join our innovative data science team.
As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying scalable machine learning pipelines into production environments.
You will work closely with data scientists and software engineers to optimise model deployment pipelines, ensure continuous integration/continuous delivery (CI/CD), and maintain model performance in a live setting.
Day to day: Design, implement, and maintain machine learning pipelines for model training, validation, and deployment.Automate end-to-end model lifecycle management, including data preprocessing, model training, testing, monitoring, and updates.Collaborate with data engineering teams to build scalable, resilient, and secure infrastructure for ML models in production.Ensure CI/CD practices for model deployment, including version control, testing, and rollback strategies.Monitor model performance, identify bottlenecks, and implement improvements to maintain optimal results.Develop tools and frameworks for the rapid deployment and iteration of machine learning models.Optimise resource usage and cost by ensuring efficient model inference and serving architectures.Maintain and improve data pipelines, ensuring data quality, availability, and integrity.Collaborate with cross-functional teams to understand business needs and translate them into actionable ML solutions.Ensure compliance with data privacy and security standards in model handling and deployment.About You: Proficiency in Python and TensorFlow, PyTorch, or other relevant ML libraries.Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for ML deployment.Strong understanding of CI/CD pipelines, containerisation (Docker, Kubernetes), and orchestration tools.Experience with monitoring tools like Datadog, Grafana, or similar to track model performance.Knowledge of infrastructure-as-code tools like Terraform or CloudFormation.Experience with version control (Git) and workflow automation.Familiarity with distributed data systems like Spark, Hadoop, or Kubernetes.Strong problem-solving skills and a commitment to continuous learning.Excellent communication skills, both written and verbal.Nice to have: Experience with A/B testing and model validation techniques.Knowledge of feature store management and model registry systems.Why Join Health Innovation Labs? Impact: Build solutions that transform healthcare and improve lives.Growth: Continuous learning, career development, and leadership opportunities.Culture: Inclusive, innovative, and mission-driven environment.Flexibility: Remote work options and focus on work-life balance.
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