About the Role
Develop and maintain scalable backend infrastructure for AI-driven applications, focusing on high-performance data processing, model integration, and system architecture.
Responsibilities
- Design and implement backend services for AI model training and inference
- Optimize data pipelines for efficiency and throughput
- Collaborate with research teams to integrate machine learning models
- Ensure system reliability and fault tolerance
- Write clean, maintainable, and well-tested code
- Monitor and improve system performance under heavy load
- Work closely with frontend and DevOps teams for seamless deployment
- Troubleshoot production issues and implement fixes
- Contribute to architectural decisions and technical planning
- Maintain documentation for systems and APIs
- Implement authentication and authorization mechanisms
- Support data storage and retrieval at scale
- Refactor legacy components for better performance
- Participate in code reviews and technical discussions
- Stay current with advancements in backend and AI technologies
Nice to Have
- Experience with large-scale data processing frameworks
- Knowledge of TensorFlow or PyTorch model deployment
- Background in machine learning engineering
- Experience with real-time data streaming
- Familiarity with monitoring and observability tools
Compensation
Competitive salary with equity and benefits
Work Arrangement
Hybrid remote with optional office locations
Team
Small, focused team working on foundational AI systems
Tech Stack
Python, FastAPI, PostgreSQL, Redis, Kafka, Docker, Kubernetes, AWS, GCP
Impact
Your work will directly shape the infrastructure powering next-generation AI capabilities
Available for qualified candidates
