Principal Mlops Platform Engineer
hace 7 meses
**Principal MLOps Platform Engineer**:
**Barcelona**
**Competitive Salary + Benefits**
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.
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.
As an **MLOps Platform Engineer** interested in building complex systems, you will be responsible for inventing how we use technology, machine learning, and data to enable the productivity of AstraZeneca. You will help design, build, and deploy our next-generation platforms and tools at scale.
**Key Accountabilities**
- Collaborate with Data Scientists and Machine Learning Engineers from across the company to understand their challenges and work with them to build the platform that underpins their research, from model experimentation to industrialization.
- Be a part of a hard-working agile team, continuously improving AstraZeneca’s enterprise Machine Learning development environments, platforms, and tooling.
- 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.
**Leadership and Collaboration**
- Ability to drive conversations and collaborate with product managers, data scientists, and other collaborators to align technical solutions with business objectives.
- Strong leadership and interpersonal skills to lead cross-functional technical teams effectively.
- Ability to coach junior technical members.
**Technical Leadership and Expertise**
- Strong analytical and problem-solving skills to address challenges.
- Solid and creative technical leadership skills to drive detailed design and fact-based decision-making.
- Strong ability to create and communicate designs to engineers that are scalable and efficient AI platforms; implement and maintain the infrastructure and platforms that support the development and deployment of AI solutions.
- Experience in DevOps/MLOps/AIOps practices to streamline the development and deployment processes.
- Strong programming skills in Infrastructure as Code (e.g., Terraform, CloudFormation), AWS Services, collaborative software development, programming languages used in AI such as Python, proficiency in containerization technologies like Docker, etc.; and the ability to write clean, efficient, and maintainable code.
- Familiarity with big data technologies, including Apache Spark and Hadoop, for processing and analyzing large datasets.
- Understanding of security standard methodologies in AI systems and alignment to compliance standards.
- Willingness to stay updated with the latest advancements in AI technologies through continuous learning and professional development.
- Actively contributes to the continuous improvements/roadmaps of existing AI platforms.
- BSc/MSc/PhD in Computer Science or related quantitative or analytical field.
- Demonstratable experience working with AWS.
- Experience administering a production cluster, with an understanding of operators, storage classes, and service meshes.
- Experience building and delivering software using Python and exceptional ability in other programming languages will be considered.
- Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale using Infrastructure as Code.
- Experience using DevOps to enable automation strategies.
- Experience in MLOps practices and building pipelines to accelerate and automate machine learning.
- Experience working in an Agile team with knowledge or experience in product or platform-focused delivery.
- Experience in data science/ML journey, from model experimentation to industrialization.
- Experience working with internal security standards and frameworks, especially in medical, clinical, or pharmaceutical contexts.
- Experience working with GxP-compliant life science systems.
- Creative, collaborative, and resilient.
**Required/Desired Certifications**
- AWS
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