Machine Learning Engineer

Amgen offers a remote-friendly environment in the United States with a supportive, collaborative culture and a strong focus on growth. You will join a team that backs scientist-driven work with scalable ML platforms, comprehensive benefits, stock-based incentives, and generous time off. The role emphasizes flexible work models, professional development, and a mission to advance treatments for patients living with serious illnesses.

Benefits

• Retirement and Savings Plan with generous company contributions, plus group medical, dental, and vision coverage
• Life and disability insurance and flexible spending accounts
• Discretionary annual bonus program (or field sales incentive plan where applicable)
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible

What you will do

In this role you will contribute to the development of scalable machine learning platforms and workflows that enable scientists and researchers at Amgen to build, deploy, and manage AI and ML models. You will collaborate with experienced engineers, data scientists, and domain experts to productionize ML solutions that primarily support drug discovery and development. This position is designed for engineers at an early to mid stage in their ML engineering career, with opportunities to grow alongside a talented team.

Responsibilities

• Deliver AI and ML enabled applications with deployed models spanning classical ML, natural language processing, protein language models, and large language models
• Develop and maintain ML platform capabilities including data pipelines and feature engineering workflows
• Develop and maintain model training, evaluation, and deployment pipelines
• Maintain experiment tracking and model registry systems
• Maintain model performance evaluations and monitoring
• Implement AI and ML Ops best practices, including CI/CD, infrastructure as code, monitoring, traceability and reproducibility
• Collaborate with cross-functional teams to transition from experimentation to production-grade enterprise solutions
• Build and maintain scalable, productionized MLOps solutions on cloud platforms
• Develop and deliver training content and knowledge articles to educate resident scientists on model lifecycle management best practices

Requirements

• Master’s degree
• Bachelor’s degree and 2 years of experience in Computer Science, IT, or engineering field
• Associate’s degree and 6 years in Computer Science, IT, or engineering field
• High school diploma or GED and 8 years in Computer Science, IT, or engineering field
• Software programming experience in Python, version control, and test-driven development
• Familiarity with cloud technologies (AWS preferred, Databricks)
• Hands-on experience with AI/ML model training and serving

Technologies

• Python
• Databricks
• AWS
• Azure
• MLflow
• Kubeflow
• Weights & Biases
• Terraform
• Docker
• Kubernetes
• Spark
• scikit-learn
• TensorFlow
• PyTorch
• LangChain

Details

• Location: Remote (remote)
• Salary: USD 129,654 - 175,415 per yearly

Sponsorship

Sponsorship for this role is not guaranteed.