Job Description
We are building the infrastructure for the year 2026 and beyond, and we need a visionary Lead AI Research Engineer to lead our cutting-edge initiatives in Generative AI and Autonomous Systems.
At Nexus Horizon, we are not just predicting the future; we are engineering it. You will be at the helm of our R&D division, tasked with architecting the next generation of intelligent algorithms that will redefine human-machine interaction. If you are passionate about pushing the boundaries of what is possible in Artificial Intelligence and want to leave a lasting legacy in the tech industry, this is your opportunity.
Why Join Us?
- Work on mission-critical projects with global impact.
- Competitive compensation packages and equity options.
- Access to state-of-the-art computing infrastructure.
Responsibilities
- Define the 2026 AI Roadmap: Lead the strategic vision for our AI research, identifying emerging trends in Large Language Models (LLMs) and Agentic AI to ensure our products remain at the forefront of innovation.
- Architect Scalable Systems: Design and deploy robust, scalable machine learning pipelines and neural network architectures capable of processing petabytes of data in real-time.
- Prototype and Validate: Spearhead the development of experimental prototypes, moving concepts from theory to production-grade code with rigorous testing and validation.
- Cross-Functional Leadership: Collaborate closely with product managers, data scientists, and software engineers to translate complex research findings into practical, user-centric applications.
- Mentorship & Culture: Cultivate a high-performance research culture by mentoring junior engineers and fostering a spirit of continuous learning and technical excellence.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: Minimum of 7 years of professional experience in AI research or software engineering, with at least 3 years in a lead or senior technical role.
- Technical Skills: Deep expertise in Python, PyTorch, or TensorFlow. Strong understanding of Deep Learning architectures (Transformers, GANs, RNNs).
- Problem Solving: Proven track record of solving complex, open-ended problems and delivering innovative solutions in dynamic environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.