Senior ML Engineer: Build & Deploy Scalable AI Pipelines

Pittsburgh Tomorrow; Pittsburgh (Allegheny County); Presencial; USD 110.000 - 170.000; Jornada completa

Descripción de la vacante

Pittsburgh Tomorrow is seeking a Senior Machine Learning Engineer in Pittsburgh to design, develop, train, and optimize ML models for business solutions. You will work with structured and unstructured data, implement supervised, unsupervised, and deep learning techniques, and deploy models into production environments.

The role requires 5–7 years of experience, strong Python skills, and hands-on experience with ML frameworks and cloud platforms.

Formación

• 5–7 years of experience in designing, developing, deploying, and maintaining ML models and AI-driven solutions.

Responsabilidades

• Design, develop, train, and optimize machine learning models to solve business problems.
• Perform data preprocessing, feature engineering, model selection, and evaluation.
• Develop scalable ML pipelines and integrate models into enterprise applications.
• Work with structured and unstructured datasets to identify patterns and generate insights.
• Implement supervised, unsupervised, and deep learning algorithms.
• Deploy and monitor ML models in production environments.
• Collaborate with data scientists, data engineers, architects, and business stakeholders.
• Optimize model performance, accuracy, scalability, and reliability.
• Implement model versioning, monitoring, and continuous improvement processes.
• Follow best practices for code quality, testing, documentation, and model governance.

Conocimientos

Python

ML algorithms

ML deployment

Cloud platforms

Data preprocessing

Containerization

Herramientas

Scikit-learn

TensorFlow

PyTorch

AWS

Azure

Google Cloud Platform

Docker

Kubernetes

Hadoop

Spark

Kafka

Descripción del empleo

Pittsburgh Tomorrow is seeking a Senior Machine Learning Engineer in Pittsburgh to design, develop, train, and optimize ML models for business solutions. You will work with structured and unstructured data, implement supervised, unsupervised, and deep learning techniques, and deploy models into production environments.

The role requires 5–7 years of experience, strong Python skills, and hands-on experience with ML frameworks and cloud platforms.