Machine Learning Engineer (USD Salary)

BairesHR -

A tech company focused on developing innovative solutions in artificial intelligence, data, and automation, working with global clients.

  • Capital Federal, Buenos Aires - Argentina
  • Tecnología, Sistemas y Telecomunicaciones
  • No especificado
  • Full-time | Presencial y Remoto
  • Senior
  • No especificado (Indistinto)

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Descripción del puesto

We are looking for a proactive Machine Learning Engineer to develop, deploy, and optimize AI/ML models that power critical business applications. You will work closely with data scientists, solution architects, and engineering teams to translate prototypes into scalable production systems, ensuring model reliability and performance.

📋 Key Responsibilities:

  • Develop, train, and optimize machine learning models using diverse algorithms and techniques.
  • Build and maintain data pipelines for model training and evaluation.
  • Deploy ML models at scale in cloud-native environments, ensuring scalability and reliability.
  • Monitor model performance, retrain when necessary, and troubleshoot production issues.
  • Translate data science prototypes into production-ready ML systems and collaborate on integration with applications.
  • Stay current with AI/ML trends, including Generative AI and large language models (LLMs).
  • Ensure data quality and governance compliance in model development and deployment.
  • Support AI/ML tool and platform decisions and contribute to governance processes.

Requisitos

Required Qualifications:

  • 7+ years in software engineering, data engineering, or related fields (minimum 2 years focused on AI/ML).
  • Experience deploying AI/ML solutions at scale, preferably in cloud-native environments.
  • Strong programming skills (Python, Java).
  • Familiarity with ML frameworks such as TensorFlow or PyTorch.
  • Knowledge of data pipelines, ML lifecycle, and data governance.
  • Exposure to Generative AI and LLM technologies.
  • Experience collaborating with cross-functional data science and engineering teams.
  • Advanced English.

Preferred Qualifications:

  • Experience with MLOps frameworks.
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes).
  • Master’s degree in Computer Science, Data Science, or related field.

Beneficios

  • Full-time, long-term remote position
  • Salary in USD
  • Paid time off (PTO)
  • Company-provided hardware (if needed)
  • Corporate gifts on special occasions

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