Principal Software Engineer

Amgen

Remote

Quick summary

Work type: Remote
Location: Tampa, FL
Salary: $157,020–$212,439 / yr
Posted: 6 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $188k

This role $185k

$128k most similar roles pay here $241k

This role pays less than 51% of similar roles. Most pay $161,500–$214,500 — the shaded band above. At the midpoint, this role pays about $185k versus about $188k for comparable roles.

Based on 239 similar postings.

Employer

About Amgen

Amgen is a leading biotechnology company that discovers, develops, manufactures, and delivers innovative human therapeutics, with products addressing conditions such as anemia, bone loss, inflammation, and cancer. Industry: Biotechnology & Pharmaceuticals

Amgen currently has 31 open roles on FindRole.

Listed pay typically runs $134,168–$181,521 across 30 roles with salary data.

Most-posted roles

View all roles at Amgen

At a glance

TL;DR · Principal Software Engineer

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As a Principal Software Engineer on the Information Systems team, you will lead the end-to-end design and deployment of machine learning and Generative AI solutions, ensuring scalability and reliability across large-scale initiatives. You’ll work closely with business stakeholders to translate objectives into impactful AI/ML solutions while defining evaluation frameworks for model performance and safety. Your day-to-day involves architecting scalable cloud-based platforms using AWS, GCP, or Azure, implementing MLOps practices, and mentoring junior engineers. Ideal candidates have a deep background in machine learning, experience with MLOps ecosystems like MLflow and Kubeflow, and proficiency in Python and frameworks such as PyTorch and TensorFlow. Additionally, familiarity with Responsible AI practices and advanced data engineering tools is highly valued.

Skills

AWS Kubernetes MLOps Python MLflow Docker Airflow CI/CD Generative AI PyTorch TensorFlow Hugging Face Apache Spark Apache Airflow Databricks PostgreSQL Responsible AI Advanced Evaluation Techniques Scalable Cloud-Based Platforms

What you'll do

Lead end-to-end design and delivery of machine learning and GenAI solutions.
Drive technical decisions for large-scale ML initiatives to ensure scalability and reliability.
Design advanced agentic AI systems with multi-agent architectures and autonomous decision-making.
Define evaluation frameworks for ML/GenAI systems, including safety and compliance measures.
Establish best practices in MLOps, LLMOps, and DevOps for efficient model deployment.
Architect scalable cloud-based ML platforms using AWS, GCP, or Azure.
Provide technical leadership and mentorship to junior engineers.

What we're looking for

Doctorate degree and 2 years of experience or equivalent.
Proven track record of leading production-grade ML/GenAI systems end-to-end.
Expertise in MLOps/LLMOps ecosystems including CI/CD, Docker, Kubernetes.
Strong system design skills with ability to operate independently and lead initiatives.
Demonstrated proficiency in leveraging cloud platforms for data engineering solutions.
Extensive experience designing robust evaluation and validation systems for ML models.

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