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Full-Stack AI Engineer

1 hour, 42 minutes ago
Kenya, South Africa
Full-time
Mid Level
AI Engineer
Software Development
Apache Airflow CI/CD Dagster Docker FastAPI Flask GCP HIPAA Hugging Face JavaScript Kubeflow Kubernetes Microservices MLflow MLOps 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 56

Description

  • Deploy pre-trained and fine-tuned ML/LLM models into production systems.
  • Wrap models in APIs for scalable inference and service integration.
  • Implement vector search and retrieval-augmented generation workflows.
  • Build ETL pipelines for ingesting, cleaning, transforming, and versioning data.
  • Manage datasets using cloud data warehouses and related tooling.
  • Develop front-end interfaces and dashboards that surface AI-powered features.
  • Design backend services and microservices that connect models to business logic.
  • Containerize and deploy ML services, and automate CI/CD for releases and model updates.
  • Monitor latency, cost, drift, and model performance after deployment.
  • Work with data science and product teams to productionize prototypes and scope AI features.
  • Document systems, workflows, 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.
  • Experience with MLOps practices such as Kubeflow, MLflow, Vertex AI, or SageMaker is preferred.
  • Familiarity with microservices, serverless architectures, and cost-optimized inference is preferred.
  • Comfort working U.S. client business hours with flexibility for deployments, experimentation cycles, 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 and business-driven AI solutions.

Interested in this position?

Apply directly on the company website

Apply Now

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