Job Description
We are Nexus Horizon Systems, a pioneer in next-generation autonomous intelligence. As we accelerate towards our 2026 Vision, we are seeking a visionary Senior AI Lead to architect the future of our machine learning infrastructure.
In this pivotal role, you won't just be maintaining models; you will be defining the architectural standards for the AI landscape of 2026. You will bridge the gap between cutting-edge research and scalable production systems, ensuring our platforms are not only intelligent but ethical, efficient, and future-proof.
Why join us?
- Shape the roadmap for Agentic AI and Autonomous Systems.
- Work with state-of-the-art hardware and cloud infrastructure.
- Competitive equity package and top-tier compensation.
Responsibilities
- Architect and lead the development of proprietary Large Language Models (LLMs) and Generative AI pipelines tailored for 2026 market needs.
- Oversee the end-to-end machine learning lifecycle, from experimental prototyping to large-scale deployment and MLOps implementation.
- Collaborate with cross-functional teams to integrate AI capabilities into consumer-facing products and enterprise solutions.
- Establish robust evaluation frameworks to ensure model accuracy, bias reduction, and safety compliance.
- Pioneer research into emerging AI paradigms, including multi-modal learning and edge computing applications.
- Mentor junior engineers and data scientists, fostering a culture of continuous innovation and technical excellence.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- 7+ years of professional experience in software engineering or data science, with at least 3 years in a leadership or senior architectural role.
- Deep proficiency in Python, PyTorch, TensorFlow, and modern GPU computing frameworks (CUDA, CUDA-X).
- Proven track record of deploying scalable AI systems in production environments (AWS, GCP, or Azure).
- Strong understanding of Deep Learning architectures, NLP, and reinforcement learning.
- Demonstrated experience with MLOps tools (MLflow, Kubeflow, SageMaker) and CI/CD pipelines.