Job Description
We are looking for a visionary Senior AI Engineer to join Nexus Horizon Technologies and help define the technological landscape for 2026 and beyond. As we stand on the precipice of the next industrial revolution, you will lead the development of next-generation Generative AI and Large Language Model (LLM) architectures.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable production engineering. You will work in a fast-paced, collaborative environment where innovation is not just encouraged—it is the currency. If you are passionate about building intelligent systems that will shape the future, we want to hear from you.
Why Join Us?
- Future-Ready Tech Stack: Work with the latest in PyTorch, TensorFlow, and quantum-ready cloud infrastructure.
- Impact: Your work will directly influence how businesses interact with technology in 2026 and beyond.
- Competitive Package: Comprehensive benefits including equity options and performance bonuses.
Responsibilities
- Architect and deploy scalable machine learning models tailored for high-velocity production environments.
- Lead the research and implementation of Generative AI models, focusing on efficiency, hallucination reduction, and domain adaptation.
- Collaborate with cross-functional teams of data scientists, product managers, and designers to define AI product requirements.
- Optimize existing neural networks for reduced latency and improved inference speed on edge devices.
- Mentor junior engineers and foster a culture of continuous learning and technical excellence within the AI department.
- Ensure the security, privacy, and ethical use of AI data in all deployed solutions.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- 5+ years of professional experience in Machine Learning, AI, or Data Science.
- Deep proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
- Proven track record of shipping production-grade machine learning systems.
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.