Job Description
The Future is Now.
Nexus Future Systems is pioneering the next generation of intelligent infrastructure. As a Senior AI Systems Architect, you will bridge the gap between cutting-edge generative AI models and scalable, high-performance cloud infrastructure. We are looking for a visionary leader to define our architectural roadmap and ensure our systems are resilient, efficient, and ready for the demands of 2026 and beyond.
In this role, you will collaborate with world-class researchers and engineers to deploy state-of-the-art Large Language Models (LLMs) into production environments. You will have the autonomy to innovate, the resources to build, and the responsibility to shape the future of our product ecosystem.
Why Join Us?
- Work on groundbreaking projects that define the next decade of tech.
- Competitive compensation and equity packages.
- Flexible remote-first policy with a hub in the heart of SF.
- Access to the latest hardware for AI training and inference.
Nexus Future Systems is pioneering the next generation of intelligent infrastructure. As a Senior AI Systems Architect, you will bridge the gap between cutting-edge generative AI models and scalable, high-performance cloud infrastructure. We are looking for a visionary leader to define our architectural roadmap and ensure our systems are resilient, efficient, and ready for the demands of 2026 and beyond.
In this role, you will collaborate with world-class researchers and engineers to deploy state-of-the-art Large Language Models (LLMs) into production environments. You will have the autonomy to innovate, the resources to build, and the responsibility to shape the future of our product ecosystem.
Why Join Us?
- Work on groundbreaking projects that define the next decade of tech.
- Competitive compensation and equity packages.
- Flexible remote-first policy with a hub in the heart of SF.
- Access to the latest hardware for AI training and inference.
Responsibilities
- Design, architect, and implement scalable distributed systems for high-volume AI inference and training workloads.
- Optimize deep learning models for latency, throughput, and cost-efficiency using techniques like quantization and model distillation.
- Lead architecture reviews and technical decision-making for the AI Infrastructure team.
- Collaborate with data scientists to ensure seamless integration of new models into the production pipeline.
- Establish best practices for monitoring, logging, and incident response within the ML platform.
- Define the technical roadmap for 2026, exploring edge computing and federated learning opportunities.
Qualifications
- 7+ years of software engineering experience with at least 3 years in AI/ML infrastructure or Systems Engineering.
- Deep expertise in Python, C++, and cloud-native technologies (Kubernetes, Docker, AWS/GCP).
- Strong understanding of deep learning frameworks (PyTorch, TensorFlow, JAX).
- Experience with MLOps tools (MLflow, Kubeflow) and model serving platforms (TorchServe, Triton).
- Proven track record of deploying LLMs and generative AI applications at scale.
- Excellent problem-solving skills and ability to communicate complex technical concepts to diverse stakeholders.