Job Description
Join the Architects of Tomorrow.
We are looking for a visionary Senior AI Architect to define the landscape of artificial intelligence for the year 2026 and beyond. At Nexus Future Labs, we aren't just building software; we are engineering the cognitive infrastructure of the future. You will lead a high-performance team in designing, training, and deploying next-generation generative models and autonomous agents that will redefine human-machine interaction.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade enterprise solutions. You will be responsible for the full lifecycle of our AI systems, ensuring they are scalable, ethical, and capable of solving complex, unsolved problems.
We are looking for a visionary Senior AI Architect to define the landscape of artificial intelligence for the year 2026 and beyond. At Nexus Future Labs, we aren't just building software; we are engineering the cognitive infrastructure of the future. You will lead a high-performance team in designing, training, and deploying next-generation generative models and autonomous agents that will redefine human-machine interaction.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade enterprise solutions. You will be responsible for the full lifecycle of our AI systems, ensuring they are scalable, ethical, and capable of solving complex, unsolved problems.
Responsibilities
- Architect Next-Gen Models: Design and implement scalable neural architectures for Large Language Models (LLMs) and multimodal systems tailored for 2026 capabilities.
- Optimize Inference Pipelines: Engineer high-throughput, low-latency inference systems capable of real-time processing for autonomous agents and neural interfaces.
- Autonomous Agent Orchestration: Lead the development of complex agent workflows that leverage LLMs for self-directed problem solving in dynamic environments.
- Research & Prototyping: Collaborate with our research division to prototype novel algorithms, specifically focusing on memory-augmented neural networks and reinforcement learning.
- Ethical AI Governance: Establish and enforce rigorous guidelines for AI safety, bias mitigation, and alignment to ensure responsible deployment of future technologies.
- Cloud Infrastructure: Manage and optimize our cloud-native ML infrastructure (AWS/GCP) to handle massive data workloads and distributed training tasks.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field from a top-tier institution.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years leading complex AI projects.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Kubeflow, MLflow, SageMaker).
- Modeling: Proven track record of designing, training, and fine-tuning state-of-the-art foundation models.
- System Design: Strong understanding of distributed systems, containerization (Docker/Kubernetes), and high-performance computing.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders.