Job Description
Shape the Technology Roadmap for 2026.
Nexus Horizon Labs is at the forefront of the next industrial revolution. We are building the foundational AI infrastructure and autonomous software systems that will define the year 2026 and beyond. We are looking for a visionary Senior AI & Software Engineer to join our elite R&D team and push the boundaries of what is possible.
In this role, you will not just write code; you will architect the future. You will work on cutting-edge Large Language Models (LLMs), generative AI agents, and decentralized systems that solve complex, real-world problems. If you are passionate about the intersection of artificial intelligence and scalable software engineering, we want to hear from you.
Responsibilities
- Architect & Develop: Design and implement high-performance machine learning models and backend services using Python, PyTorch, and modern cloud infrastructure.
- Future-Proofing: Research and prototype emerging technologies to ensure our platform remains ahead of the curve through 2026 and beyond.
- System Optimization: Optimize model inference latency and improve the scalability of distributed systems handling massive data loads.
- Cross-Functional Leadership: Collaborate closely with product managers, data scientists, and UX designers to translate complex requirements into robust technical solutions.
- Mentorship: Guide junior engineers and interns, fostering a culture of innovation, technical excellence, and continuous learning.
- Deployment: Oversee the CI/CD pipeline and ensure reliable deployment of models to production environments.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional software engineering experience with a strong focus on Machine Learning or AI.
- Technical Stack: Proficiency in Python, C++, or Rust. Deep understanding of PyTorch, TensorFlow, or JAX.
- AI Expertise: Strong background in Natural Language Processing (NLP), Transformers, LLMs, or Reinforcement Learning.
- Cloud & Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Problem Solving: Ability to tackle ambiguous problems and deliver creative, scalable solutions under tight deadlines.