Principal AI Engineer - Evinova, Barcelona
Empresa
AstraZeneca
Provincia
Barcelona
Ciudad
Barcelona
Tipo de Contrato
Tiempo Completo
Descripción
Principal AI Engineer - Evinova
About the role and the project:
On average, it takes more than 10 years to develop a drug and costs more than 1.3 billion. Over 70 of drug R D costs are spent on clinical development, yet the success rate from phase I to approval is only around 10 . At Evinova, a health tech business unit, we are on a mission to increase clinical trial success rates by 20 , accelerate clinical development timelines by 36 months, and reduce study costs by 50 by leveraging state-of-the-art AI and Machine Learning.
If you are a solid coder with hands-on experience developing AI and ML solutions, strong understanding of modern deep learning, robust AWS skills, and a voracious learner, then you could be a fantastic fit for our team.
Talent with ambition to grow into leadership roles will be a key differentiator for successful candidates. Glass ceiling smashers especially welcome.
We are seeking a highly skilled and innovative Principal AI Engineer to design and implement advanced machine learning models that solve complex healthcare problems. In this role, you will translate analytical prototypes into robust, scalable production systems while leading the end-to-end AI and ML lifecycle from data preparation to deployment and monitoring. Youll develop and maintain critical data pipelines, deliver production-ready code following best practices, and collaborate with cross-functional teams to deliver data-driven solutions that align AI initiatives with business objectives.
This position offers the opportunity to mentor team members, drive digital transformation in healthcare, and work with cutting-edge technologies including traditional deep learning models and modern MLOps practices. Youll be at the forefront of applying machine learning to revolutionize clinical development and drug discovery.
Accountabilities:
- Design and implement AI agentic workflows and advanced machine learning models to solve complex healthcare problems.
- Translate analytical prototypes into robust, scalable production systems.
- Lead end-to-end ML lifecycle from data preparation to deployment and monitoring.
- Develop and maintain data pipelines supporting model training and deployment.
- Deliver production ready code as well as infrastructure as code, implementing best practices for code quality, testing, and documentation.
- Collaborate with cross-functional teams to deliver data-driven solutions.
- Mentor team members with a less technical background in software engineering.
- Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation.
- Stay current with advancements in data science, AI and software engineering.
Essential Skills/Experience:
- Degree in Computer Science, Mathematics, Physics or related quantitative field.
- 5+ years in data science roles focused on production-ready solutions.
- Strong Python programming with proficiency in data science libraries such as NumPy, pandas, scikit-learn, SciPy, Optuna and TensorFlow/PyTorch.
- Extensive experience developing and deploying Python APIs, particularly using FastAPI and MCPs.
- Agentic AI frameworks for design and orchestration.
- Strong expertise in Python testing frameworks (pytest, unittest, mock)
- Experience with RESTful API design, documentation, dependency injection, error handling, and logging.
- Proficiency with AWS cloud services (CDK, EKS, S3, IAM, CloudWatch)
- CI/CD experience, particularly with GitHub Actions workflows.
- Advanced SQL skills and experience with graph databases.
- Docker containerization and Kubernetes orchestration experience.
- Experience working with AI tools and Large Language Models (LLMs) for practical applications.
- Creative problem-solving abilities and outside-the-box thinking.
- Excellent communication skills for technical and non-technical audiences.
- Proven collaborative team experience.
- Demonstrated innovation mindset and ability to work independently.
Desirable Skills/Experience:
- AWS Machine Learning Engineer or AWS Solution Architect certification.
- TypeScript or a similar strongly-typed programming language experience.
- Data visualisation expertise.
- Experience with real-time data processing and streaming.
- Performance testing experience with data-intensive applications.
- Front-end development familiarity.
- Knowledge of healthcare AI/ML regulatory requirements.
- Knowledge of drug development and previously experience of working in pharmaceutical industrial.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. Thats why we work, on average, a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
Python, NumPy, pandas, scikit
About the role and the project:
On average, it takes more than 10 years to develop a drug and costs more than 1.3 billion. Over 70 of drug R D costs are spent on clinical development, yet the success rate from phase I to approval is only around 10 . At Evinova, a health tech business unit, we are on a mission to increase clinical trial success rates by 20 , accelerate clinical development timelines by 36 months, and reduce study costs by 50 by leveraging state-of-the-art AI and Machine Learning.
If you are a solid coder with hands-on experience developing AI and ML solutions, strong understanding of modern deep learning, robust AWS skills, and a voracious learner, then you could be a fantastic fit for our team.
Talent with ambition to grow into leadership roles will be a key differentiator for successful candidates. Glass ceiling smashers especially welcome.
We are seeking a highly skilled and innovative Principal AI Engineer to design and implement advanced machine learning models that solve complex healthcare problems. In this role, you will translate analytical prototypes into robust, scalable production systems while leading the end-to-end AI and ML lifecycle from data preparation to deployment and monitoring. Youll develop and maintain critical data pipelines, deliver production-ready code following best practices, and collaborate with cross-functional teams to deliver data-driven solutions that align AI initiatives with business objectives.
This position offers the opportunity to mentor team members, drive digital transformation in healthcare, and work with cutting-edge technologies including traditional deep learning models and modern MLOps practices. Youll be at the forefront of applying machine learning to revolutionize clinical development and drug discovery.
Accountabilities:
- Design and implement AI agentic workflows and advanced machine learning models to solve complex healthcare problems.
- Translate analytical prototypes into robust, scalable production systems.
- Lead end-to-end ML lifecycle from data preparation to deployment and monitoring.
- Develop and maintain data pipelines supporting model training and deployment.
- Deliver production ready code as well as infrastructure as code, implementing best practices for code quality, testing, and documentation.
- Collaborate with cross-functional teams to deliver data-driven solutions.
- Mentor team members with a less technical background in software engineering.
- Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation.
- Stay current with advancements in data science, AI and software engineering.
Essential Skills/Experience:
- Degree in Computer Science, Mathematics, Physics or related quantitative field.
- 5+ years in data science roles focused on production-ready solutions.
- Strong Python programming with proficiency in data science libraries such as NumPy, pandas, scikit-learn, SciPy, Optuna and TensorFlow/PyTorch.
- Extensive experience developing and deploying Python APIs, particularly using FastAPI and MCPs.
- Agentic AI frameworks for design and orchestration.
- Strong expertise in Python testing frameworks (pytest, unittest, mock)
- Experience with RESTful API design, documentation, dependency injection, error handling, and logging.
- Proficiency with AWS cloud services (CDK, EKS, S3, IAM, CloudWatch)
- CI/CD experience, particularly with GitHub Actions workflows.
- Advanced SQL skills and experience with graph databases.
- Docker containerization and Kubernetes orchestration experience.
- Experience working with AI tools and Large Language Models (LLMs) for practical applications.
- Creative problem-solving abilities and outside-the-box thinking.
- Excellent communication skills for technical and non-technical audiences.
- Proven collaborative team experience.
- Demonstrated innovation mindset and ability to work independently.
Desirable Skills/Experience:
- AWS Machine Learning Engineer or AWS Solution Architect certification.
- TypeScript or a similar strongly-typed programming language experience.
- Data visualisation expertise.
- Experience with real-time data processing and streaming.
- Performance testing experience with data-intensive applications.
- Front-end development familiarity.
- Knowledge of healthcare AI/ML regulatory requirements.
- Knowledge of drug development and previously experience of working in pharmaceutical industrial.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. Thats why we work, on average, a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
Python, NumPy, pandas, scikit