below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$202,187–$254,750.
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
76 open roles
on FindRole.
Listed pay typically runs
$136,906–$185,227
across 45 roles with salary data.
The Machine Learning Engineer joins the AI Studio team within the AI & Data Science organization to transform high-value business challenges into scalable AI products. You will independently own production components, including model services, data pipelines, retrieval components, and agent tools. Responsibilities include designing, implementing, and supporting maintainable components with clear contracts, testing, and documentation. You will build GenAI, NLP, and RAG systems using structured output, embeddings, and hybrid search while engineering batch or event-driven pipelines with schema validation. Key technologies include Python, SQL, PyTorch, TensorFlow, Hugging Face, Scikit-learn, AWS, Databricks, and Spark. You will apply supervised and unsupervised methods, feature engineering, and observability to solve complex problems in a regulated healthcare environment, ensuring compliance with GxP controls and Responsible AI standards.
What does a Machine Learning Engineer earn in Remote?
Median $246638 from 41 postings across 11 companies.
Design and implement maintainable Python and SQL components for APIs, data, models, and workflows.
Build GenAI, NLP, RAG, and bounded agent components using structured output and hybrid search.
Engineer batch or event-driven data pipelines with schema validation, lineage, and access control.
Define evaluation metrics for model quality, uncertainty, retrieval, grounding, safety, and latency.
Release and support components using cloud services, containers, CI/CD, and monitoring tools.
Apply security, privacy, Responsible AI, and GxP controls to all production components.
Diagnose complex technical failures and provide incident response and runbooks.
Guide associate engineers on familiar work and contribute reusable assets to the enterprise.
What we're looking for
Must have a Master’s degree, or a Bachelor’s degree with 2 years of experience, or an Associate’s degree with 6 years of experience, or a high school diploma with 8 years of experience in Computer Science, IT, or a related field.
Must have strong hands-on proficiency in Python and SQL with sound software-engineering and testing practices (preferred).
Must have strong capability in at least one of classical ML, GenAI/RAG/agents, or MLOps/platform engineering with working knowledge of adjacent areas (preferred).
Must have experience with PyTorch, TensorFlow, Hugging Face, scikit-learn, XGBoost, PyMC, computer vision, NLP, GNNs, causal inference, or uncertainty estimation (preferred).
Must have experience with AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, infrastructure as code, MLflow, Airflow, Kubeflow, or GitHub Actions (preferred).
Must have experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, hybrid retrieval, knowledge graphs, graph RAG, or evidence verification (preferred).
Must have experience in healthcare, life sciences, GxP, validated systems, or another regulated or high-impact environment (preferred).
Must have experience in production software and AI/ML system design, including APIs, background jobs, event flows, testing, performance, observability, and source control (preferred).
Python
Java
C++
MLOps
DevOps
Natural Language Processing
Deep Learning
Computer Vision
Docker
Kubernetes
Infrastructure-as-Code
AWS
Azure
Linux
UNIX
Cloud-native
Data Science
Data Analytics