ML Engineer: Build & Deploy Production AI Pipelines

Carbon Data Solutions; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

AbbVie is seeking an experienced ML Engineer to own components of ML systems from design to production delivery. You will translate requirements into clean, maintainable code and build robust data pipelines and feature workflows to support machine learning and AI initiatives.

The role requires strong Python skills, experience with ML libraries and MLOps practices, and collaboration across data scientists and engineers. Remote-friendly environment and scalable architectures are emphasized.

Qualifications

• Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, OR a quantitative field.
• 3+ years of practical experience building, evaluating, scaling, and deploying ML pipelines with Python.
• Strong programming skills in Python and solid understanding of core CS principles.
• Experience with data manipulation frameworks such as Pandas and PySpark.
• Experience with ML libraries such as scikit-learn, HuggingFace, TensorFlow/Keras, PyTorch, or MLlib.
• Experience with MLOps practices such as automated model deployment and monitoring.
• Working knowledge of SQL and relational data structures.
• Ability to design, train, and evaluate ML models using standard best practices.

Responsibilities

• Own small to medium ML components from design through deployment.
• Translate requirements into high-quality, maintainable code and deliver workstreams on plan.
• Build and maintain data pipelines and feature engineering workflows for ML/AI solutions.
• Design, train, evaluate, and refine ML models with sound statistical practices.
• Deploy ML solutions as microservices, APIs, batch jobs, or streaming components.
• Support production monitoring with metrics for performance, drift, anomalies, and retraining triggers.
• Collaborate with data engineers, software engineers, data scientists, and stakeholders.
• Understand system design and data models to contribute to implementation decisions.
• Follow governance and version control standards consistently.
• Document progress, decisions, and outcomes to both technical and non-technical audiences.

Skills

Python

ML pipelines

SQL

Spark/PySpark

Cloud AWS

MLOps

Data manipulation

APIs/microservices

Education

BS/MS/PhD in a quantitative field

Tools

Pandas

PyTorch

TensorFlow/Keras

scikit-learn

Docker

Kubernetes

Job description

AbbVie is seeking an experienced ML Engineer to own components of ML systems from design to production delivery. You will translate requirements into clean, maintainable code and build robust data pipelines and feature workflows to support machine learning and AI initiatives.

The role requires strong Python skills, experience with ML libraries and MLOps practices, and collaboration across data scientists and engineers. Remote-friendly environment and scalable architectures are emphasized.