Associate Principal Full Stack ML Engineer – Ev...
Are you ready to revolutionize the world of clinical trials? At Evinova, part of the AstraZeneca Group, we're on a mission to transform drug development by leveraging cutting-edge AI and Machine Learning. With the goal of increasing clinical trial success rates by 20%, accelerating timelines by 36 months, and slashing study costs by 50%, we need innovative minds like yours!If you're a skilled coder with a passion for developing ML solutions, a deep understanding of modern deep learning, and robust AWS skills, this could be your chance to make a significant impact. We're looking for ambitious individuals eager to grow into leadership roles and break through glass ceilings. Join us as a Associate Principal (Associate Director) Full Stack ML Engineer to design and implement advanced machine learning models that tackle complex healthcare challenges. You'll lead the end-to-end ML lifecycle, develop critical data pipelines, and collaborate with cross-functional teams to align AI initiatives with business objectives.This is your opportunity to mentor team members, drive digital transformation in healthcare, and work with state-of-the-art technologies.Accountabilities
- Design and implement advanced machine learning models and agentic systems 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.
- Degree in Computer Science, Mathematics, Physics or related quantitative field.
- Strong prior experience 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 delivery of genAI 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.
- 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.