Principal Machine Learning Engineer - Evinova at AstraZeneca

Santanyí, Balearic Islands, Spain -

Full Time

Start Date

Immediate

Expiry Date

02 Jan, 26

Salary

0.0

Posted On

04 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, AWS, MLOps, APIs, SQL, Docker, Kubernetes, Deep Learning, CI/CD, Data Pipelines, Collaboration, Mentoring, Problem Solving, Communication

Industry

Pharmaceutical Manufacturing

Description

Introduction to role Are you ready to revolutionize the future of healthcare? At Evinova, part of the AstraZeneca Group, we're on a mission to transform clinical trials with cutting-edge AI and Machine Learning. With the goal of increasing success rates by 20%, accelerating timelines by 36 months, and reducing costs by 50%, we are redefining the landscape of drug development. If you're a skilled coder with a passion for innovation and a desire to lead, this is your chance to make a significant impact. Join us as we design advanced machine learning models that tackle complex healthcare challenges and drive digital transformation in the industry. We are seeking a highly skilled and innovative Principal Machine Learning 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 ML lifecycle from data preparation to deployment and monitoring. You'll 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. You'll be at the forefront of applying machine learning to revolutionize clinical development and drug discovery. Accountabilities - Design and implement 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. - 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 visualization 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 previous experience working in the pharmaceutical industry is nice to have but not required. 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. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. At AstraZeneca, we embrace change and invest in technology to redefine healthcare. Our dynamic environment supports innovation through collaboration and creativity. With access to cutting-edge tools and a global network of experts, we drive meaningful change in predicting, preventing, and treating patient conditions. Our commitment to lifelong learning empowers us to make an impact worldwide. Ready to be part of this transformative journey? Apply now and help shape the future of healthcare! Date Posted 03-oct-2025 Closing Date 16-oct-2025 AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

Responsibilities

Design and implement advanced machine learning models to solve complex healthcare problems while leading the end-to-end ML lifecycle. Collaborate with cross-functional teams to deliver data-driven solutions that align AI initiatives with business objectives.