Senior ML Engineer: Cloud, MLOps & LLMs

GCS Recruitment; Philadelphia (Philadelphia County); Presencial; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

GCS Recruitment is seeking a Machine Learning Engineer to join a high-performing AI and Data Science team in the United States. You will design end-to-end ML pipelines, build scalable predictive models, and operationalize ML workloads in a cloud environment.

The ideal candidate has strong Python, PySpark, Scikit-learn expertise, and experience with AWS and MLOps. Familiarity with LLMs/NLP and deployment in enterprise systems is highly desired.

Formación

• 5+ years of experience in Machine Learning Engineering or AI engineering.
• Strong programming experience in Python.
• Hands-on PySpark and large-scale data processing.
• Experience developing ML models with Scikit-learn.
• Experience building MLOps pipelines, deployment, and monitoring.
• Familiarity with AWS cloud environments and LLMs/NLP.

Responsabilidades

• Design, develop, and deploy ML models for predictive analytics and BI use cases.
• Build scalable data processing and feature pipelines with PySpark.
• Develop, test, and optimize ML algorithms using Python and Scikit-learn.
• Implement end-to-end MLOps pipelines for training, deployment, and monitoring.
• Collaborate with data scientists, engineers, and stakeholders to productionize ML solutions.
• Leverage AWS to build scalable ML infrastructure and enable LLM integration.

Conocimientos

Python

PySpark

Scikit-learn

AWS

MLOps

LLMs / NLP

CI/CD

PyTorch

TensorFlow

Herramientas

CI/CD

PyTorch

TensorFlow

Descripción del empleo

GCS Recruitment is seeking a Machine Learning Engineer to join a high-performing AI and Data Science team in the United States. You will design end-to-end ML pipelines, build scalable predictive models, and operationalize ML workloads in a cloud environment.

The ideal candidate has strong Python, PySpark, Scikit-learn expertise, and experience with AWS and MLOps. Familiarity with LLMs/NLP and deployment in enterprise systems is highly desired.