Senior AI/ML Production Engineer (Python & MLOps)
Location: Remote (EU)
Contract: 12 months | Daily Rate Contract
Industry: Life Sciences / Clinical Research
Our client, a global life sciences organisation headquartered in Dublin, Ireland, is seeking an experienced Senior AI/ML Production Engineer to join their growing technology team on an initial 12-month contract.
This is a hands-on engineering role focused on taking AI and machine learning models developed by Data Science teams and transforming them into scalable, reliable, production-ready solutions.
Working closely with Data Scientists, Software Engineers and Cloud Architects, you will play a key role in bridging the gap between experimental models and enterprise production environments, supporting AI-driven applications and data processing within clinical research.
Key Responsibilities
Productionise AI/ML Models: Take Python-based prototypes, algorithms and machine learning models from research environments and develop them into robust, scalable production services.
Software Engineering: Design, develop and optimise Python applications, REST APIs, microservices and automated data pipelines to support AI/ML workloads.
MLOps & Automation: Build and maintain CI/CD and MLOps pipelines covering automated testing, model deployment, versioning, monitoring and reproducibility.
Performance Optimisation: Refactor and optimise existing Python code to improve execution speed, memory efficiency, reliability and scalability when processing large, complex datasets.
Cloud & Infrastructure: Deploy and integrate AI/ML solutions within AWS and/or Azure environments, leveraging containerisation and orchestration technologies.
Monitoring & Reliability: Implement production monitoring, logging, telemetry and model performance tracking to identify issues and maintain system reliability.
Cross-functional Collaboration: Work closely with Data Science, Engineering and Cloud teams to translate experimental solutions into maintainable, production-grade applications.
Security & Compliance: Apply secure engineering practices and support relevant data privacy and regulatory requirements within clinical and life sciences environments.
Skills & Experience
5+ years of professional software engineering experience, including significant hands-on experience deploying and supporting AI/ML solutions in production.
Strong Python engineering expertise , including writing clean, maintainable, well-tested and performance-optimised code.
Proven experience taking machine learning models or Python-based analytical applications from prototype through to production deployment.
Experience developing REST APIs, microservices and backend applications using frameworks such as FastAPI or Flask.
Hands-on experience with MLOps, CI/CD and automated deployment , using tools such as MLflow, Databricks, Kubeflow, Airflow, DVC or similar.
Strong experience with AWS and/or Azure , including Docker, Kubernetes and cloud-native deployment practices.
Good understanding of machine learning workflows, model lifecycle management, monitoring and production troubleshooting.
Experience working with SQL databases, data pipelines and large-scale data processing environments.
Familiarity with modern software engineering practices, including Git, automated testing, code reviews and infrastructure automation.
Desirable Experience
Experience working with PyTorch, TensorFlow, scikit-learn or other machine learning frameworks.
Exposure to distributed processing technologies such as Apache Spark or Databricks.
Experience optimising computationally intensive Python workloads or large-scale data pipelines.
Familiarity with model monitoring, data drift detection and ML observability.
Previous experience within life sciences, pharmaceuticals, clinical research, healthcare or other regulated environments .
Understanding of GDPR, GxP or other relevant data governance and compliance requirements.
The Opportunity
This is an opportunity to work on…