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Lead Full-Stack ML Engineer, Healthcare AI Innovator

ASTRAZENECA UK LIMITED

City of Westminster

On-site

GBP 60,000 - 85,000

Full time

Yesterday
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Job summary

A leading healthcare company in the UK seeks a Full Stack ML Engineer to revolutionize clinical trials through advanced machine learning solutions. The role includes designing and implementing ML models, leading the ML lifecycle, and collaborating with cross-functional teams. Candidates should have a background in computer science, strong Python programming skills, and experience with AWS cloud services. This position offers a chance to drive digital transformation in healthcare and mentor team members, contributing to a significant impact on drug development timelines and costs.

Qualifications

  • Solid knowledge of Python and experience with machine learning models.
  • Strong background in creating production-ready data science solutions.
  • Proficiency in AWS services for cloud-based deployments.

Responsibilities

  • Design and implement advanced machine learning models.
  • Lead the ML lifecycle from data preparation to deployment.
  • Collaborate with cross-functional teams to deliver solutions.

Skills

Python programming
Data science libraries (NumPy, pandas, scikit-learn)
AWS cloud services
CI/CD with GitHub Actions
SQL
Docker containerization
Communication skills
Creative problem-solving

Education

Degree in Computer Science, Mathematics, or related field

Tools

FastAPI
TensorFlow
Kubernetes
Job description
A leading healthcare company in the UK seeks a Full Stack ML Engineer to revolutionize clinical trials through advanced machine learning solutions. The role includes designing and implementing ML models, leading the ML lifecycle, and collaborating with cross-functional teams. Candidates should have a background in computer science, strong Python programming skills, and experience with AWS cloud services. This position offers a chance to drive digital transformation in healthcare and mentor team members, contributing to a significant impact on drug development timelines and costs.
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