Job Description
We are at the forefront of the artificial intelligence revolution, preparing our infrastructure for the demands of 2026 and beyond. Apex Neural Systems is seeking a visionary AI Infrastructure Lead to architect the next generation of scalable, resilient, and high-performance machine learning ecosystems.
In this role, you will bridge the gap between cutting-edge AI research and robust, enterprise-grade engineering. You will define the architectural standards that will power our products through the 2026 landscape, ensuring we remain ahead of the curve in an increasingly competitive market.
Why Join Us?
• Impactful Work: Build the backbone of systems that will define the future of AI.
• Future-Proofing: Focus on technologies and architectures specifically designed for the 2026 era.
• Top-Tier Team: Collaborate with world-class researchers and engineers.
Responsibilities
- Design and implement scalable AI infrastructure architectures capable of supporting 10x model growth by 2026.
- Optimize deep learning pipelines for high-throughput, low-latency inference in production environments.
- Lead the migration and integration of next-generation hardware accelerators (e.g., advanced GPU/TPU clusters).
- Establish and enforce best practices for MLOps, data governance, and model versioning.
- Conduct architectural reviews to ensure system resilience, security, and scalability.
- Collaborate with data science teams to translate research prototypes into robust, production-ready services.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks.
- Proven track record of architecting large-scale cloud infrastructure (AWS, GCP, or Azure).
- Strong understanding of Kubernetes, Docker, and microservices architecture.
- Experience with hardware acceleration and performance tuning on GPU clusters.
- Excellent communication skills and the ability to lead technical initiatives across cross-functional teams.