Senior ML Engineer — Cloud, MLOps & LLMs

GCS Recruitment

Reston (VA)

Presencial

USD 120.000 - 180.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

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

The role emphasizes Python, PySpark, Scikit-learn, MLOps, and experience with AWS and LLMs. You will collaborate with data scientists and engineers to deploy production-ready ML solutions and continuously improve model performance.

Formación

  • 5+ years in ML engineering or related roles.
  • Strong Python programming.
  • Hands-on PySpark and large-scale data processing experience.
  • Experience with Scikit-learn and ML pipelines.
  • Experience with AWS and cloud ML deployments.
  • Familiar with LLMs / NLP and Generative AI.

Responsabilidades

  • Design, develop, and deploy ML models for predictive analytics and BI use cases.
  • Build scalable data processing and feature engineering pipelines with PySpark.
  • Develop, test, and optimize ML algorithms using Python and Scikit-learn.
  • Implement and maintain end-to-end MLOps pipelines for training, deployment, monitoring, and lifecycle management.
  • Collaborate with data scientists, software engineers, and stakeholders to translate requirements into production ML solutions.
  • Leverage AWS to build scalable ML infrastructure and deploy models into production.

Conocimientos

Python
PySpark
Scikit-learn
MLOps
AWS
LLMs
Data analysis
Statistical modeling
CI/CD
Communication skills

Herramientas

PyTorch
TensorFlow

Descripción del empleo

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

The role emphasizes Python, PySpark, Scikit-learn, MLOps, and experience with AWS and LLMs. You will collaborate with data scientists and engineers to deploy production-ready ML solutions and continuously improve model performance.

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