Job Description
We are building the future of artificial intelligence, and we are looking for a visionary Senior AI Engineer 2026 to lead our next-generation initiatives. In this role, you won't just be writing code; you will architect the neural networks and machine learning models that will define the digital landscape of the coming decade.
Nexus Horizons is at the forefront of generative AI and sustainable computing. We are seeking a technical leader who thrives in ambiguity and possesses an unparalleled drive to push the boundaries of what is possible. If you are ready to tackle complex challenges and leave a lasting legacy in the tech world, we want to meet you.
Why Join Us?
• Work with state-of-the-art hardware and cloud infrastructure.
• Competitive equity package and benefits.
• Flexible remote and hybrid work options.
• Professional development and learning stipends.
Responsibilities
- Architect Next-Gen AI Systems: Design, develop, and deploy scalable machine learning models and deep neural networks with a focus on AGI readiness.
- Optimization & Efficiency: Drive performance optimization for large-scale inference and training pipelines, ensuring low latency and high throughput.
- Research & Innovation: Stay at the bleeding edge of AI research, experimenting with novel architectures and methodologies to solve industry-specific problems.
- Collaboration: Partner with cross-functional teams including product managers, data scientists, and engineers to translate business requirements into technical solutions.
- Code Review & Mentorship: Maintain high code quality standards through rigorous code reviews and mentor junior developers and researchers.
- Roadmap Leadership: Contribute to the technical roadmap for 2026, identifying key technologies and tools that will drive our product roadmap.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering, with a proven track record of deploying production-level AI systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed systems and cloud computing (AWS/GCP/Azure).
- AI Expertise: Deep knowledge of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Exceptional ability to debug complex issues and optimize algorithms for performance and accuracy.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.