Job Description
At Nexus Future Labs, we are at the forefront of defining the technological landscape for the year 2026 and beyond. We are seeking a visionary Senior AI Architect to spearhead our mission in Artificial General Intelligence (AGI) and next-generation neural computing. If you are a technical leader who thrives in a fast-paced, high-stakes environment and wants to build the systems that will define the future, we want to meet you.
As a key member of our engineering leadership team, you will not just write code; you will architect the very fabric of our AI ecosystem. We are looking for someone who combines deep technical expertise with the ability to communicate complex concepts to diverse stakeholders.
Responsibilities
- Design and architect scalable, fault-tolerant AI infrastructure aligned with our 2026 roadmap.
- Lead research and development in generative models, transformer architectures, and reinforcement learning.
- Collaborate with product managers and researchers to define technical vision and product specifications.
- Establish and enforce best practices for code quality, security, and ethical AI usage.
- Mentor senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Optimize existing models for inference speed and resource efficiency in cloud environments.
- Stay abreast of the latest advancements in the AI field to drive technological innovation internally.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 7+ years of professional experience in software engineering and machine learning.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven experience deploying and scaling large-scale machine learning models in production.
- Deep understanding of deep learning architectures, including Transformers, GNNs, and diffusion models.
- Experience with MLOps tools (Kubeflow, MLflow) and cloud platforms (AWS, GCP, or Azure).
- Excellent problem-solving skills and the ability to work autonomously in a remote-first environment.