This is a remote position.

Design and implement robust, scalable, and secure backend services for AI-powered products
Work closely with data scientists and ML engineers to integrate models into production systems
Build and optimize APIs, microservices, and data pipelines for real-time and batch processing
Ensure low-latency inference, efficient model deployment, and resource management
Maintain and improve CI/CD pipelines, containerization (Docker/Kubernetes), and cloud infrastructure
Monitor, debug, and optimize backend systems for performance, scalability, and reliability
Collaborate with cross-functional teams to define system architecture and technical standards
Stay current with AI infrastructure trends, tools, and best practices

5+ years of backend software development experience, ideally in Python, Go, or Java
2+ years of experience deploying and scaling machine learning models in production
Solid understanding of RESTful APIs, gRPC, message queues, and microservice architectures
Experience with ML frameworks (e.g., TensorFlow, PyTorch, ONNX) and serving tools (e.g., TorchServe, Triton, FastAPI)
Strong knowledge of Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure)
Familiarity with data pipelines, distributed systems, and model versioning (MLflow or similar)
Proficiency in SQL and NoSQL databases (e.g., PostgreSQL, Redis, MongoDB)

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Compétences