Job Description
We are not just predicting the future; we are architecting it. Nexus Horizon Labs is seeking a visionary Senior AI & Future Tech Engineer to lead our initiatives in Generative AI and Autonomous Systems. As we gear up for the transformative year of 2026, we need a pioneer who thrives on ambiguity and can build the core infrastructure that will define the next generation of human-machine interaction.
In this role, you will bridge the gap between theoretical AI research and scalable production systems. You will work on cutting-edge Large Language Models (LLMs), reinforcement learning agents, and ethical AI frameworks that push the boundaries of what's possible today.
Responsibilities
- Architect Future-Proof Systems: Design and deploy scalable machine learning pipelines capable of handling billions of data points, ensuring longevity and adaptability for 2026 and beyond.
- Lead Model Development: Spearhead the development and fine-tuning of proprietary Generative AI models, focusing on reasoning, context retention, and multimodal outputs.
- Autonomous Agent Integration: Build intelligent agents that can autonomously execute complex workflows, optimizing our internal operations and client deliverables.
- Ethical AI Governance: Implement rigorous safety guidelines and bias mitigation strategies to ensure our AI systems are transparent, fair, and responsible.
- Research & Prototyping: Stay at the forefront of the industry by exploring emerging paradigms such as Neuromorphic Computing or Quantum Machine Learning concepts.
- Cross-Functional Leadership: Collaborate with product, design, and engineering teams to translate futuristic concepts into tangible, high-impact products.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Technical Mastery: Deep expertise in Python, PyTorch, TensorFlow, and modern LLM frameworks (Hugging Face, LangChain).
- Experience: 5+ years of experience in machine learning engineering, with a strong portfolio of deployed production models.
- Algorithmic Expertise: Proficiency in Deep Learning, Natural Language Processing (NLP), and Reinforcement Learning.
- System Design: Demonstrated ability to design distributed systems with high availability, fault tolerance, and low latency.
- Creativity: A "future-first" mindset with the ability to navigate unstructured problems and define new technical standards.