Job Description
Shape the Future of Intelligence
Horizon 2026 Labs is at the forefront of defining the technological landscape for the year 2026 and beyond. We are seeking a visionary Lead AI Architect to design and deploy scalable, autonomous AI systems that will power the next generation of human-machine interaction.
What You Will Do
As a Lead AI Architect, you will be responsible for the end-to-end design of our core neural infrastructure. You will bridge the gap between theoretical research and production-grade engineering, ensuring our systems are robust, ethical, and future-proof.
Key Responsibilities
- Architect and implement next-generation Generative AI models, including Large Language Models (LLMs) and multimodal systems.
- Lead a team of data scientists and engineers in the research and deployment of autonomous decision-making algorithms.
- Optimize neural network performance for low-latency, high-throughput environments using distributed computing.
- Establish best practices for AI ethics, bias mitigation, and safety in automated systems.
- Collaborate with product leaders to translate complex technical concepts into scalable product features.
- Oversee the integration of quantum-ready algorithms into our existing cloud infrastructure.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 8+ years of professional experience in machine learning engineering, with at least 3 years in a leadership or architect role.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Deep understanding of Transformer architectures, Reinforcement Learning, and NLP.
- Proven track record of deploying AI systems that handle high-volume data streams.
- Strong grasp of cloud-native technologies (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
Why Join Us?
Be part of a team that is not just adapting to the future, but creating it. We offer competitive compensation, equity packages, and a flexible remote-first culture designed for high-performance innovators.
Responsibilities
- Architect and implement next-generation Generative AI models, including Large Language Models (LLMs) and multimodal systems.
- Lead a team of data scientists and engineers in the research and deployment of autonomous decision-making algorithms.
- Optimize neural network performance for low-latency, high-throughput environments using distributed computing.
- Establish best practices for AI ethics, bias mitigation, and safety in automated systems.
- Collaborate with product leaders to translate complex technical concepts into scalable product features.
- Oversee the integration of quantum-ready algorithms into our existing cloud infrastructure.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 8+ years of professional experience in machine learning engineering, with at least 3 years in a leadership or architect role.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Deep understanding of Transformer architectures, Reinforcement Learning, and NLP.
- Proven track record of deploying AI systems that handle high-volume data streams.
- Strong grasp of cloud-native technologies (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).