Job Description
The Opportunity
OmniVerse Technologies is pioneering the next generation of artificial intelligence infrastructure. We are looking for a visionary Lead AI Architect to lead our 2026 Strategic Initiative, a groundbreaking project aimed at redefining the scalability and ethics of generative AI models. You will be responsible for architecting the core systems that will power the next decade of human-machine interaction.
Why Join Us?
- Work at the intersection of cutting-edge research and real-world application.
- Competitive compensation package including equity.
- Flexible remote-first culture with hubs in SF and NYC.
Key Responsibilities
- Architect and design scalable, high-performance AI systems tailored for the 2026 roadmap.
- Lead the technical strategy for deploying large-scale neural networks across distributed cloud environments.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical specifications.
- Ensure system reliability, security, and compliance with emerging AI governance standards.
- Mentor junior engineers and foster a culture of continuous innovation.
- Drive the integration of novel hardware accelerators (GPUs/TPUs) into software pipelines.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related technical field.
- Minimum 8 years of experience in software engineering, with a strong focus on Machine Learning systems.
- Deep expertise in Python, C++, and distributed computing frameworks (Ray, Spark, Kubernetes).
- Proven experience designing architectures for LLMs and Large-Scale Data Pipelines.
- Strong understanding of system optimization, latency reduction, and model quantization.
- Excellent communication skills with the ability to translate complex technical concepts for stakeholders.
Skills
Python, PyTorch, TensorFlow, Distributed Systems, Kubernetes, AWS, GCP, System Design, Machine Learning Operations (MLOps)
Category
Information Technology
Responsibilities
- Architect and design scalable, high-performance AI systems tailored for the 2026 roadmap.
- Lead the technical strategy for deploying large-scale neural networks across distributed cloud environments.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical specifications.
- Ensure system reliability, security, and compliance with emerging AI governance standards.
- Mentor junior engineers and foster a culture of continuous innovation.
- Drive the integration of novel hardware accelerators (GPUs/TPUs) into software pipelines.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related technical field.
- Minimum 8 years of experience in software engineering, with a strong focus on Machine Learning systems.
- Deep expertise in Python, C++, and distributed computing frameworks (Ray, Spark, Kubernetes).
- Proven experience designing architectures for LLMs and Large-Scale Data Pipelines.
- Strong understanding of system optimization, latency reduction, and model quantization.
- Excellent communication skills with the ability to translate complex technical concepts for stakeholders.