Senior Machine Learning Engineer

Amgen

Remote

Quick summary

Work type
Remote
Location
TX
Salary
$156,190–$211,315 / yr
Posted
3 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $217k
This role $184k
$144k most similar roles pay here $274k

This role pays less than 73% of similar roles. Most pay $183,625–$249,750 — the shaded band above. At the midpoint, this role pays about $184k versus about $217k for comparable roles.

Based on 240 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 $136,173–$184,235 across 30 roles with salary data.

Most-posted roles

View all roles at Amgen

At a glance

TL;DR · Senior Machine Learning Engineer

Role Posting Log in to save

As a Senior Machine Learning Engineer on our dynamic team, you will be responsible for developing and scaling machine learning models from development to production, collaborating closely with data scientists and engineers to create efficient ML pipelines using cloud platforms like AWS, GCP, or Azure. Your day-to-day tasks include building MLOps pipelines, implementing DevOps best practices, and monitoring model performance through tools such as MLflow, Kubeflow, and Airflow. You will also conduct A/B testing and stay updated with the latest advancements in machine learning. Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn is essential, along with experience in MLOps practices and DevOps tools like Docker and Kubernetes. This role involves working on large-scale data processing and analysis, making it ideal for someone passionate about solving complex business problems through cutting-edge technology.

Skills

AWS Kubernetes Docker CI/CD MLflow Kubeflow Airflow Python TensorFlow PyTorch Scikit-learn MLOps Prometheus Grafana

What you'll do

  • Develop and train machine learning models in collaboration with data scientists.
  • Build and maintain MLOps pipelines for efficient model deployment and monitoring.
  • Automate ML workflows using DevOps/MLOps best practices and tools.
  • Implement cloud-based solutions for ML model development and deployment.
  • Conduct A/B testing to optimize the performance of machine learning models.
  • Stay updated with advancements in machine learning and related technologies.

What we're looking for

  • Solid foundation in machine learning algorithms and techniques.
  • Experience with MLOps practices and tools (MLflow, Kubeflow, Airflow).
  • Proficiency in Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn).
  • Expertise in cloud platforms for ML model development and deployment.
  • Strong analytical skills and ability to implement monitoring systems.
  • Experience in DevOps/MLOps best practices and automation tools.
  • Good communication and collaboration skills with cross-functional teams.

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