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Full-Stack AI Engineer

16 hours, 48 minutes ago
Mexico, Argentina, Brazil, Colombia, Peru
Full-time
Mid Level
AI Engineer
Software Development
Apache Airflow CI/CD Dagster Docker FastAPI Flask GCP HIPAA Hugging Face JavaScript Kubeflow Kubernetes Machine Learning 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 30

Description

  • Deploy pre-trained and fine-tuned ML and LLM models into production systems.
  • Wrap models in APIs to support scalable inference and integration with business logic.
  • Implement vector search and retrieval-augmented generation components.
  • Build ETL pipelines to ingest, clean, transform, label, preprocess, and version data.
  • Store and manage datasets in cloud data warehouses.
  • Develop front-end interfaces that surface AI features such as chatbots, dashboards, and analytics.
  • Design back-end services and microservices that connect models to applications.
  • Containerize services and deploy them to Kubernetes-based environments.
  • Automate CI/CD workflows for model updates and application releases.
  • Monitor latency, cost, drift, uptime, and model performance after deployment.
  • Work with data scientists and product teams to productionize prototypes and prioritize AI features.
  • Document workflows, systems, and results for reproducibility and knowledge transfer.

Requirements

  • 3+ years of software engineering experience with exposure to AI/ML.
  • Proficiency in Python with PyTorch and TensorFlow.
  • Proficiency in JavaScript/TypeScript with React and Node.js.
  • Experience deploying ML 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 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 deployment, experimentation, and sprint schedules.

Benefits

  • Full-time remote position.
  • Flexible working hours aligned to U.S. client business hours.
  • Opportunity to work on production AI applications with real business impact.

Interested in this position?

Apply directly on the company website

Apply Now

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