Sr Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Aug 3, 2026. Amgen scores A on the Alion truth index.
Career Category
ManufacturingJob Description
Sr Machine Learning Engineer
ABOUT AMGEN
Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, making people’s lives easier, fuller, and longer. We discover, develop, manufacture, and deliver innovative medicines to help millions of patients. Amgen helped establishthe biotechnology industry more than 40 years ago and remainson the cutting edgeof innovation, using technology and human genetic data to push beyond what’sknown today.
ABOUT THE ROLE
Role Description:
Let’sdo this. Let’schange the world. We are looking for a highly motivated expert Data Engineer to design and developscalable, secure, and reliable data pipelines and ingestion solutions that power knowledge layersand assistant experiencesviagenerative AI solutions for our Manufacturing Applications Product Team. The ideal candidate will be responsible fordesigning, developing, and optimizingdata pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics for Manufacturing and Operations usecases. This role requires deep expertisein big data processing, distributed computing, data modeling,LLMs, vector stores,productizedassistant workflows.and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management.
Roles & Responsibilities
Design, develop, and maintaincomplex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets.
Champion ML/LLM feature engineeringincluding dataingestion, embeddings/vector DBs, RAG/LLM serving, latencyoptimization,and knowledgegraph/metadata.
Build highly efficient data pipelines to migrate and deploy complex data across systems, with an understanding of biotech/pharma/manufacturing or related domains.
Design and implement solutions to enable secure access, logging, privacycontrols.unified data access, governance, and interoperability across hybrid cloud environments.
Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB, etc.), APIs, logs, event streams, images, PDFs, and third-party platforms.
Ensure data integrity, accuracy, and consistency through rigorous quality checks and monitoring.
Innovate, explore, and implement new tools and technologies to enhance efficient data processing.
Proactively identifyand implement opportunities to automate tasks and develop reusable frameworks.
Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value.
Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories.
Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle.
Collaborate and communicate effectively with product teams and cross-functional teams to understand business requirements and translate them into technical solutions.
Must-Have Skills
Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL, Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies.
Proficiencyin workflow orchestration and performance tuningon big data processing.
Strong understanding of AWS services.
Ability to quickly learn, adapt, and apply new technologies.
Strong problem-solving and analytical skills.
Excellent communication and teamwork skills.
Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.
Experience with streaming technologies such as Apache Kafka, Debezium, or similar platforms for real-time data processing and integration.
Good-to-Have Skills
Experience with AI assistedcode development using tools like GitHub Copilot, Cursor, Claude Code.
Collaboration with ML engineers, prompt engineers, Product Managersand Owners.
Data engineering experience in biotechnology or pharma industry.
Experience inwriting APIs to make data available to consumers.
Experience with SQL/NoSQL databases,vector databases for large language models.
Experience with data modeling and performance tuning for both OLAP and OLTP databases.
Experience with software engineering best practices, including version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven, etc.), automated unit testing, and DevOps.
Experience with manufacturing related data sources like SCADA,Data Historian is a plus
Education and Professional Certifications
Doctorate Degree OR
Master’s degree with 4 - 6 years of experience in Computer Science, ITor related field OR
Bachelor’s degree with 6 - 8 years of experience in Computer Science, ITor related field
Soft Skills
Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills.
Ability to work effectively with global, virtual teams.
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented, with a focus on achieving team goals.
Ability to learn quickly, be organized, and detail-oriented.
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