FCamara Consulting & Training

AI Engineer

FCamara Consulting & Training

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇧🇷 Brazil

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Job Level

Mid-LevelSenior

Tech Stack

AirflowAWSAzureCloudDockerGoogle Cloud PlatformGraphQLJenkinsKubernetesNoSQLPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

  • Collaborate with the AI Solutions Architect to translate business requirements into scalable and efficient ML/AI models and pipelines.
  • Implement AI models, validate their performance, and ensure integration with existing architectures.
  • Develop robust data pipelines: data collection, processing, model training, and deployment.
  • Integrate AI solutions into production environments, following MLOps best practices (monitoring, automation, scalability), with knowledge of MLflow or platforms such as AzureML or Google Vertex AI.
  • Work closely with commercial and product teams to prototype and validate proposals, delivering iteratively and focusing on customer-centered solutions.
  • Actively participate in assessing technical risks (performance, scalability, security) and collaborate on implementing preventive solutions.
  • Ensure efficient use of cloud tools (AWS, Azure, GCP) in solution development and deployment.
  • Collaborate on creating technical documentation and best practices in alignment with the architect and other stakeholders.

Requirements

  • Experience in developing and deploying Machine Learning and Deep Learning models.
  • Proficiency in programming languages such as Python (TensorFlow, PyTorch, Scikit-learn, Pandas).
  • Experience with MLOps and CI/CD tools (MLflow, Kubeflow, Jenkins, GitLab CI).
  • Strong experience with SQL and NoSQL databases and query optimization practices.
  • Experience with cloud computing services (AWS, Azure, or GCP) and containers (Docker, Kubernetes).
  • Familiarity with system architectures, data pipelines, and API integration best practices (REST, GraphQL).
  • Nice-to-have / Differentials:
  • Experience with Generative AI and large language models (LLMs) (e.g., GPT, BERT).
  • Experience with cloud orchestration tools such as Airflow, Data Factory, or Databricks Pipelines.
  • Experience with Docker, Docker Compose, Kubernetes, or related tools such as Azure Container Apps.
  • Experience working in agile environments (Scrum, Kanban).
  • Experience collaborating on projects with solution architects or commercial teams.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
Machine LearningDeep LearningPythonTensorFlowPyTorchScikit-learnPandasSQLNoSQLMLOps
Soft skills
collaborationcustomer-centered solutionstechnical risk assessmentcommunicationiterative delivery
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