Vaga de parceiro

Machine Learning Engineer - Espírito Santo / RN

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Detalhes da Vaga

  • Escolaridade Não Informado
  • Segmento Não Informado
  • Salário Não Informado
  • Área de AtuaçãoDiversos / Outros

O que você irá fazer

  • 12 months contract.
  • About the RoleWe are looking for an experienced MLOps Engineer to bridge the gap between machine learning (ML) development and production deployment.
  • In this role, you will design, build, and maintain scalable ML infrastructure, automate model deployment, and ensure the reliability of ML models in production environments.
  • You will work closely with Data Scientists, ML Engineers, and DevOps teams to streamline workflows and improve the operationalization of AI / ML solutions.
  • Key ResponsibilitiesDevelop and maintain CI / CD pipelines for ML model deployment and monitoring.
  • Design and implement scalable ML infrastructure using cloud services (AWS, GCP, or Azure).
  • Automate model training, validation, and deployment using tools like Kubeflow, MLflow, or TensorFlow Serving.
  • Implement model versioning, tracking, and governance frameworks to ensure reproducibility and compliance.
  • Optimize ML workloads for performance, cost efficiency, and scalability.
  • Monitor model drift, retrain pipelines, and manage data versioning to ensure continued model accuracy.
  • Collaborate with Data Scientists to streamline experimentation and productionization workflows.
  • Ensure security, governance, and compliance of ML models in production environments.
  • Work with Kubernetes, Docker, and Terraform to manage ML infrastructure.
  • Develop alerting and monitoring systems for ML models using tools like Prometheus, Grafana, or Datadog.
  • RequirementsEducation & Experience :Bachelors or Masters in Computer Science, Data Engineering, or a related field.
  • 3+ years of experience in MLOps, DevOps, or ML Engineering.
  • Technical Skills :Proficiency in Python and / or Go.
  • Experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Strong understanding of containerization (Docker) and orchestration (Kubernetes).
  • Hands-on experience with cloud platforms (AWS / GCP / Azure) and serverless architectures.
  • Knowledge of CI / CD tools (GitHub Actions, Jenkins, ArgoCD, or CircleCI).
  • Experience with ML pipeline orchestration tools (Kubeflow, Apache Airflow, or MLflow).
  • Understanding of model monitoring, logging, and performance optimization.
  • Soft Skills :Ability to collaborate with cross-functional teams.
  • Strong problem-solving and analytical skills.
  • Passion for automation and continuous improvement.
  • Nice-to-Have SkillsExperience with feature stores (Feast, Tecton).
  • Knowledge of compliance standards like GDPR, HIPAA (if applicable).
  • Why Join Us?Work on cutting-edge ML infrastructure at scale.
  • Collaborate with top AI / ML experts in a fast-paced environment.
  • #J-18808-Ljbffr

Informações Adicionais

  • Quantidade de Vagas 1
  • Jornada Não Informado
 

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