Principal MLOps Platform Engineer
Location: Barcelona
Salary: Competitive Salary + Benefits
Job Description Role
The Enterprise AI Platforms and Technologies Team is responsible for building and running the platforms, tooling, and infrastructure that powers AstraZeneca's ambition to use AI in every step of the value chain, from discovering new compounds to patient safety systems.
We achieve this through technical leadership and agile-focused development, continuously evaluating the fast-moving advancements in Machine Learning tooling for challenges across AstraZeneca's R&D, Commercial, and Operations domains.
We deliver these tools through easy-to-access environments, allowing AstraZeneca's Data Scientists and Machine Learning Engineers to focus on building groundbreaking solutions for patients at scale.
We seek an MLOps Platform Engineer to join our Enterprise AI Platforms and Technologies Team.
The ideal candidate will have strong software engineering principles and experience in deploying and maintaining complex projects, preferably in the ML domain.
You will be part of a collaborative team of multidisciplinary engineers and have the chance to create tools that will advance the standard of healthcare, improving the lives of millions of patients across the globe.
Our data science platforms will support major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning-led drug discovery, and software as a medical device system.
Key Accountabilities: Develop and maintain scalable and robust cloud-based software applications.Collaborate with data scientists, product managers, designers, and other engineers to create innovative software engineering solutions geared towards ML.Write clean, efficient code, participate in code reviews, ensure application performance, and solve software issues.Work closely and collaboratively with internal multi-functional teams (governance, compliance, Cyber Security, Data Privacy, etc.)
to secure our estate without obstructing end-user productivity.Qualifications:
We understand that not everyone has the same background, and we encourage you to apply even if you don't meet every qualification listed.
Here's what we're looking for:
Strong demonstrable experience in Python.Considerable exposure to cloud computing (preferably AWS but open to others).Experience in DevOps/MLOps/AIOps practices to streamline the development and deployment processes.Solid and creative technical leadership skills to drive detailed design and fact-based decision-making.Proficiency in containerization technologies like Docker, Kubernetes and orchestration tools like Argo workflows, Kubeflow etc.An interest in machine learning and experience with frameworks like TensorFlow, PyTorch, or Scikit-learn.Understanding of security standard methodologies in AI systems and alignment to compliance standards.
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