Job Description
The Future is Now. Join Apex Horizon as we architect the AI systems for the year 2026 and beyond.
We are on a mission to redefine the boundaries of artificial intelligence. As we scale our core infrastructure, we are seeking a visionary Lead AI Infrastructure Engineer to build the robust, scalable, and secure systems that will power our next-generation applications. This role is not just about maintaining current systems; it is about pioneering the architecture that will define the AI landscape in 2026.
As part of our elite engineering team, you will work with state-of-the-art hardware and software stacks, collaborating with researchers to deploy models that push the envelope of performance and efficiency.
Responsibilities
- Architect and maintain high-performance AI infrastructure optimized for 2026 workload demands.
- Design scalable deep learning pipelines capable of handling petabyte-scale data processing.
- Lead the deployment and optimization of Large Language Models (LLMs) on distributed cloud and edge computing environments.
- Implement best practices for MLOps, ensuring continuous integration and delivery of AI models with zero-downtime updates.
- Collaborate with data science teams to translate research into production-grade, fault-tolerant systems.
- Drive technical strategy for hardware acceleration, including GPU/TPU cluster management and resource allocation.
Qualifications
- Master’s degree or PhD in Computer Science, Electrical Engineering, or a related technical field.
- 8+ years of experience in software engineering with at least 4 years specifically in AI/ML infrastructure or systems engineering.
- Deep proficiency in Python, C++, and CUDA for high-performance computing.
- Extensive experience with Kubernetes, Docker, and cloud platforms (AWS, GCP, or Azure) in AI workloads.
- Proven track record of deploying large-scale ML models in production environments.
- Strong understanding of distributed systems theory, concurrency, and fault tolerance.