Machine Learning Engineer at Amgen Capability Center, Lisbon, Portugal

Career Category: Information Systems

Job Description

Join Our Team and Defy Imagination

The Amgen Capability Center (ACCP) in Lisbon, Portugal, is a dynamic hub with over 300 multi-national and multi-cultural employees. Our team covers a broad spectrum of functions, including Commercial, General and Administrative, Research and Development, and more. The ACCP offers significant career growth opportunities, international exposure, and the chance to thrive in one of Europe’s most attractive cities. We are proud to be ranked as the #1 company from 201-500 employees by the Great Place to Work Institute in Portugal.

Our office is located at Maleo – Sete Rios, Av. José Malhoa 19, 1070-040 Lisbon, right in the vibrant city center.

At Amgen, our mission to serve patients drives everything we do. We are global collaborators dedicated to researching, manufacturing, and delivering innovative products that reach over 10 million patients worldwide. It’s time for a career you can be proud of. Join us as a Machine Learning Engineer.

Your Role and Responsibilities

LIVE - What You Will Do

Are you passionate about using machine learning to shape the future of healthcare? As a Machine Learning Engineer at Amgen, you will be an integral part of our Decision Sciences team. You will work closely with data scientists to develop and deploy advanced machine learning algorithms. Here's what you can expect:

• Collaborate with data scientists to create scalable frameworks, state-of-the-art tools, and efficient code.
• Assist in the design and architecture of machine learning systems, ensuring seamless integration into production environments.
• Optimize code for efficiency and scalability, keeping up-to-date with the latest technological advancements.
• Communicate complex technical concepts to non-technical stakeholders, ensuring clear understanding and alignment with business objectives.

Your specific responsibilities will include:

• Execute machine learning models and code with attention to quality and consistency.
• Work on the entire lifecycle of cD&A machine learning projects, from ideation to maintenance.
• Provide robust frameworks, tools, and infrastructure support for machine learning algorithms.
• Contribute to the design and architecture of scalable and robust machine learning systems.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers.
• Stay current with advancements in machine learning, artificial intelligence, and related technologies.
• Assist in data acquisition and preprocessing strategies, working closely with data engineers.

WIN - What We Expect from You

Our ideal candidate is a team player with a customer-focused attitude. You should be problem-solving oriented, with strong time and process management skills.

Requirements:

• Master’s degree or Bachelor’s degree with 2 years of machine learning experience.
• Degree in computer science, engineering, mathematics, healthcare, or related field.
• Fluency in English, both written and oral.

Preferred Qualifications:

• Deep expertise in Python, including writing efficient and maintainable code for machine learning applications.
• Proficiency in PySpark for large-scale data processing and analysis.
• Understanding of the end-to-end machine learning lifecycle.
• Experience with cloud platforms like AWS, GCP, or Azure.
• Proficiency with version control systems like Git.
• Strong analytical and problem-solving skills.
• Keen attention to detail in coding, model evaluation, and data analysis.
• Excellent communication skills for conveying technical concepts.

THRIVE - What You Can Expect from Us

At Amgen, you'll find vast opportunities to learn, develop, and move up and across our global organization. You'll be part of a diverse and inclusive community that encourages innovation and collaboration. Our Total Rewards Plan includes comprehensive healthcare, financial, and career benefits. We also offer flexible work arrangements to support your work-life balance.

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