Job Description
Are you ready to architect the future? Nexus Horizon Labs is pioneering the next generation of Artificial General Intelligence, and we are looking for a visionary Senior AI Engineer to lead our Project 2026 initiative.
In this role, you won't just write code; you will define the architectural roadmap that will power the AI landscape a decade from now. We are seeking a deep thinker who thrives in ambiguity and has a passion for pushing the boundaries of what's possible with Large Language Models (LLMs), Generative AI, and scalable neural architectures.
Why join us?
- Impact: Work on core models that will be adopted by millions of users globally.
- Autonomy: We offer a high degree of creative freedom and technical ownership.
- Equity: Competitive RSU package and performance bonuses tied to Project 2026 milestones.
If you are looking to build the infrastructure for tomorrow, today, apply now.
Responsibilities
- Architectural Leadership: Design and implement scalable, robust AI infrastructure capable of handling billions of inference requests with sub-millisecond latency.
- Model Development: Spearhead the research and deployment of next-generation transformer architectures and reinforcement learning algorithms.
- System Optimization: Identify bottlenecks in training pipelines and inference engines, implementing solutions to improve efficiency and cost-effectiveness.
- Collaboration: Partner closely with Product Managers and Data Scientists to translate abstract research concepts into production-ready features.
- Mentorship: Guide a team of talented ML engineers, fostering a culture of continuous learning and innovation.
- Future-Proofing: Stay ahead of the curve on emerging AI trends (e.g., Neuro-symbolic AI, Multimodal learning) to ensure Project 2026 remains at the forefront of the industry.
Qualifications
- Experience: 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior or lead capacity.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Ray, Apache Spark).
- AI Expertise: Proven track record of working with LLMs (GPT, LLaMA, Claude) and fine-tuning models for specific domains.
- Education: M.S. or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field (preferred).
- Problem Solving: Exceptional ability to solve complex, unstructured problems with elegant, scalable solutions.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.