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Senior MLOps Platform Engineer

AstraZeneca

Barcelona

Híbrido

EUR 55.000 - 75.000

Jornada completa

Hace 5 días
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Descripción de la vacante

A global biopharmaceutical company is seeking an ML Ops engineer based in Barcelona. You will collaborate with data scientists to develop tools that enhance machine learning projects and improve the efficiency of AI initiatives. Candidates should have a degree in Computer Science and relevant experience in software engineering and automation. The role involves adapting standard methods to modern environments and requires a proactive, collaborative approach. Join us in making a meaningful impact in the field of biopharma.

Formación

  • Demonstrable experience delivering machine learning projects at scale.
  • 3+ years experience building software in Python or related languages.
  • Experience in Agile environments.

Responsabilidades

  • Collaborate with Data Scientists and Machine Learning Engineers.
  • Improve Machine Learning development environments and platforms.
  • Ensure compliance while enhancing end-user productivity.

Conocimientos

Software engineering
Automation
Collaboration
Machine Learning

Educación

Bsc, MSc or Ph.D. degree in Computer Science or related field

Herramientas

Python
Container orchestration frameworks (e.g. Airflow, Argo, Kubeflow)
Descripción del empleo
Role Barcelona based- 3 days at office/ 2 days at home

AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies.

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.

ABOUT OUR ENTERPRISE AI PRODUCTS AND TECHNOLOGY TEAM

Place to do important work. We connect across the whole business to power each function to better influence patient outcomes and improve their lives. Impactful and valuable, this is where you come to raise your profile and do good for others. Play an increasingly crucial role in driving disruptive transformation on our journey to becoming a digital and data‑led enterprise. Unleash the power of our latest innovations in data, machine learning and technology to turn complex information into life‑changing and practical insights. Work in synergy with leading experts in our specialist communities. Here we bring the brightest minds to bear, with access to cutting‑edge techniques and the opportunity to be part of novel solutions. It’s up to us to drive the outcomes forward, inventing and building, expanding our knowledge to identify the next opportunity. An inclusive team, we bring together diverse areas – different functions as well as external partners. Pooling from an unrivalled source of knowledge, we share, learn and challenge. It powers us to decode business needs and apply our technical know‑how to add greater value. Rise to the challenge of shaping the future of an evolving business in the technology space.

ABOUT THE ROLE

The Enterprise AI Products and Technology Team are 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 are looking for an ML Ops engineer to join our Enterprise AI Products and Technology Team. The ideal candidate will have industry‑relevant experience delivering at scale Machine Learning or Data Science projects. You will be part of a collaborative team of multidisciplinary engineers and will work closely with data science teams, creating tools, standards and automating commonly used tasks of the machine learning product lifecycle. A part of the role is also to increase the capabilities of the platforms team to better suit the data scientist ways of working. Our data science teams undertake major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning‑led drug discovery, software as a medical device system.

As an ML Ops engineer, you have a software engineering mindset towards automation and agility while being able to question and improve the ways of working of data science teams.

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 tools/platforms that underpin their research.
  • Be a part of a high performing agile team, continuously improving AstraZeneca’s Machine Learning development environments, platforms and tooling to better suit data science initiatives.
  • Work closely and collaboratively with internal governance and compliance functions such as Cyber Security and Data Privacy to secure our estate without obstructing end‑user productivity.
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
  • Champion “production‑first mindset” in the data science project development lifecycle to seamlessly scale exploratory research to production.
Candidate Knowledge, Skills and Experience
  • Bsc, MSc or Ph.D. degree in Computer Science or related quantitative or analytical field.
  • Demonstrable experience in software engineering and automation leveraging DevOps.
  • Prior experience with developing and deploying production‑grade machine learning products or exceptional ability in other software engineering domains will be considered.
  • 3 years or more of experience building and delivering software using the Python programming language; exceptional ability in other programming languages will also be considered.
  • In depth knowledge and experience with at least one container orchestration framework (Airflow, Argo, Kubeflow, etc.) or willingness to learn.
  • Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at scale using Infrastructure as Code.
  • Experience working in an Agile team.
  • Experience working within internal security standards and frameworks.
  • Creative, collaborative and resilient.
WHY JOIN IT?

We’re a network of entrepreneurial self‑starters who contribute to something far bigger. There’s a diversity of expertise in our Technology group that’s unique to AstraZeneca – it allows us to dive deep into exploring new leading‑edge technology. We enable AstraZeneca to perform at its peak by delivering world‑class technology and data solutions. Our work unlocks the potential of science. We optimise and evolve AstraZeneca by maximising efficiencies and finding new ways to drive productivity, from automation to data simplification. We’re not afraid to take ownership and run with it. Empowered with unrivaled freedom. A place to be open and transparent – we speak up, think creatively and share ideas. Our diverse contributions help us to make better decisions. But we have a constant drive to innovate, and an appreciation for high standards. It takes challenging the status quo to add value in our ever‑evolving environment. We love it here because, put simply, we make a meaningful impact.

Date Posted: 09-dic-2025

Closing Date: 30-dic-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.

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