Applied AI Engineer - GenAI Studio

BioSpace; Washington (District of Columbia); On-site; USD 140,000 - 200,000; Full time

Job summary

Amgen is seeking a Machine Learning Engineer for the AI Studio to join a fun, innovative engineering team. You will own defined production components, connecting model, data, and workflow parts to measurable business impact.

Responsibilities include building Python/SQL modules, APIs, and agents, implementing evaluation and monitoring, and ensuring robust security and governance across AI assets. Collaboration with cross-functional teams is essential.

Qualifications

• Master's degree in a relevant field or equivalent industry experience.
• Strong Python/SQL and software engineering practices.
• Experience with GenAI, NLP, or ML model development and deployment.
• Exposure to cloud services, MLOps, and responsible AI concepts.

Responsibilities

• Define component boundaries, acceptance criteria and estimates with partners.
• Design and implement Python, SQL, API and workflow components with tests.
• Apply ML methods, feature engineering and evaluation techniques.
• Build GenAI, NLP and bounded agent components with proper provenance.
• Develop data and embedding pipelines with validation and access control.
• Define evaluation criteria for model quality and safety.
• Release and support components using cloud services, CI/CD and monitoring.
• Apply security, privacy and governance in AI assets; mentor junior engineers.

Skills

Python

SQL

Software engineering

Testing practices

CI/CD

Cloud services

Security/Privacy

Responsible AI

Education

Masters degree

Bachelors degree + 2 years CS/IT

Associates degree + 6 years CS/IT

High school diploma / GED + 8 years CS/IT

Tools

PyTorch

TensorFlow

Hugging Face

scikit-learn

LangChain

Kubernetes

Job description

Amgen is seeking a Machine Learning Engineer for the AI Studio to join a fun, innovative engineering team. You will own defined production components, connecting model, data, and workflow parts to measurable business impact.

Responsibilities include building Python/SQL modules, APIs, and agents, implementing evaluation and monitoring, and ensuring robust security and governance across AI assets. Collaboration with cross-functional teams is essential.