Remote AI Software Engineer — Deploy, Optimize & Scale ML

Hire Feed; Alessandria; Remoto; EUR 55.000 - 90.000; Tempo pieno

Descrizione del lavoro

Hire Feed is seeking a remote AI Machine Learning Engineer to design, implement, and optimize AI-powered software deployed in production. This role offers global collaboration and requires strong software engineering practices.

You will work with Python, C++, or Java; TensorFlow, PyTorch, or ONNX Runtime; Docker and Kubernetes for deployment; and CI/CD workflows to ensure scalable, reliable AI services.

Competenze

• Experience with AI software development using frameworks (TensorFlow, PyTorch, ONNX).
• Proficiency in Python, C++, or Java for performance-critical apps.
• Knowledge of model deployment strategies (Docker, Kubernetes).
• Familiarity with AI infra (GPUs/TPUs, cloud AI services).
• Understanding of software engineering best practices (Git, CI/CD, Agile).
• Experience with API design/integration for AI services (REST, gRPC, GraphQL).
• Ability to analyze and optimize AI model performance in production.

Mansioni

• Design, develop, and maintain AI software components (inference engines, pipelines, APIs).
• Optimize AI models for latency, throughput, and scalability in production.
• Collaborate with data scientists to translate models into production software.
• Implement robust testing frameworks for AI software functionality and reliability.
• Document architecture decisions and deployment processes for stakeholders.

Conoscenze

TensorFlow

PyTorch

ONNX Runtime

Python

C++

Java

REST

gRPC

GraphQL

Git

CI/CD

Agile

Performance optimization

AI model deployment

Docker

Kubernetes

GPU/TPU

Strumenti

Docker

Kubernetes

Descrizione del lavoro

Hire Feed is seeking a remote AI Machine Learning Engineer to design, implement, and optimize AI-powered software deployed in production. This role offers global collaboration and requires strong software engineering practices.

You will work with Python, C++, or Java; TensorFlow, PyTorch, or ONNX Runtime; Docker and Kubernetes for deployment; and CI/CD workflows to ensure scalable, reliable AI services.