Job Description
Are you ready to architect the technological breakthroughs that will define the year 2026? Horizon 26 Technologies is seeking a visionary Senior AI Engineer to lead our core research division. We are building the infrastructure for the next generation of generative AI, autonomous systems, and quantum-ready algorithms.
In this role, you won't just be maintaining legacy systems; you will be building the future. We are looking for a thought leader who understands the trajectory of AI development and can translate that vision into scalable, production-grade code.
Why Join Us?
At Horizon 26, we prioritize innovation over convention. Our team is dedicated to solving complex problems that will shape the landscape of technology for the foreseeable future. You will have the autonomy to experiment with cutting-edge tools and the resources to push the boundaries of what is possible.
Responsibilities
- Architect Next-Gen Neural Architectures: Design and implement state-of-the-art machine learning models capable of handling the massive data loads expected in 2026.
- Lead AI Strategy: Define the technical roadmap for AI capabilities, ensuring alignment with the company's vision for the 2026 product suite.
- Optimize Model Performance: Continuously monitor, evaluate, and improve the accuracy and efficiency of deployed models to ensure real-time processing.
- Collaborate on Interdisciplinary Projects: Work closely with data scientists, software engineers, and product managers to integrate AI solutions seamlessly into the user experience.
- Mentor Junior Engineers: Foster a culture of learning and technical excellence by providing guidance and code reviews to the engineering team.
- Ensure Ethical AI Standards: Implement guidelines and safeguards to ensure AI outputs are fair, transparent, and unbiased.
Qualifications
- Advanced Technical Expertise: Master's degree in Computer Science, Mathematics, or a related field (PhD preferred) with 5+ years of experience in Machine Learning and Deep Learning.
- Programming Proficiency: Strong command of Python and frameworks such as TensorFlow, PyTorch, or Keras.
- Cloud Architecture: Experience deploying and managing large-scale AI models on cloud platforms like AWS, GCP, or Azure.
- NLP & GenAI Knowledge: Deep understanding of Natural Language Processing (NLP) and experience with Large Language Models (LLMs).
- Problem-Solving Skills: Ability to tackle unstructured problems and devise innovative algorithmic solutions.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.