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Full-Stack AI Engineer

1 hour, 5 minutes ago
Mexico, Argentina, Brazil, Colombia, Peru
Full-time
Mid Level
Full-stack Engineer
Software Development
Apache Airflow CI/CD Dagster Docker FastAPI Flask GCP HIPAA Hugging Face JavaScript Kubeflow Kubernetes Microservices MLflow Next.js Node.js Prefect Python PyTorch React SageMaker Serverless Snowflake SQL TensorFlow TypeScript Vertex AI Vue.js
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Pavago

Pavago

Pavago specializes in connecting small and medium-sized businesses with skilled offshore talent from Pakistan and Latin America, offering a streamlined recruitment process that enables the hiring, onboarding, and payment of remote employees at signific...

IT Services
Founded 2023
View All Jobs 59

Description

  • Deploy pre-trained and fine-tuned machine learning and LLM models into production systems.
  • Wrap models in APIs for scalable inference and integrate vector search for retrieval-augmented generation workflows.
  • Build ETL pipelines to ingest, clean, transform, label, preprocess, and version data.
  • Store and manage datasets in cloud data warehouses.
  • Develop front-end interfaces for AI-powered features such as chatbots, dashboards, and analytics.
  • Design back-end services and microservices that connect models to business logic.
  • Containerize ML services and deploy them to Kubernetes-based environments.
  • Automate CI/CD pipelines for model updates and application releases.
  • Monitor latency, cost, model drift, and overall system performance after deployment.
  • Collaborate with data science and product teams to productionize prototypes and scope AI features.

Requirements

  • 3+ years of software engineering experience with exposure to AI/ML.
  • Proficiency in Python, including PyTorch and TensorFlow.
  • Proficiency in JavaScript or TypeScript, including React and Node.js.
  • Experience deploying machine learning models into production systems.
  • Strong SQL skills and experience with cloud data warehouses.
  • Experience with LLM fine-tuning, embeddings, and RAG pipelines is preferred.
  • Knowledge of MLOps tools and practices such as Kubeflow, MLflow, Vertex AI, or SageMaker is preferred.
  • Familiarity with microservices, serverless architectures, and cost-optimized inference is preferred.
  • Ability to work U.S. client business hours with flexibility for deployments, experimentation cycles, and sprint schedules.

Interested in this position?

Apply directly on the company website

Apply Now

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