Job Description
We are building the systems that will define the year 2026. At Nexus Future Labs, we are not just predicting the future; we are engineering it. We are seeking a visionary Senior AI Architect to spearhead our R&D division, defining the core models that will power our next generation of intelligent systems.
In this pivotal role, you will bridge the gap between theoretical research and production engineering, ensuring our AI solutions are scalable, secure, and revolutionary. If you are passionate about the intersection of generative AI, large language models, and long-term strategic planning, we want to meet you.
Why Join Us?
- Impact: Directly influence the technological landscape of 2026.
- Growth: Work with cutting-edge hardware and software stacks.
- Equity: Competitive stock options in a Series A-funded unicorn.
Responsibilities
- Strategic Leadership: Own the technical vision for the 2026 product roadmap, defining how generative AI will integrate into our core platforms.
- Model Development: Design and implement cutting-edge Large Language Models (LLMs) and multimodal architectures tailored for enterprise scalability.
- System Optimization: Lead the charge in reducing inference latency and improving model accuracy for real-time, high-volume applications.
- R&D Collaboration: Partner with product managers and data scientists to translate abstract 2026 concepts into deployable, production-ready code.
- Team Mentorship: Foster a culture of innovation, mentoring junior engineers and data scientists on best practices in deep learning and MLOps.
- Security & Ethics: Implement rigorous guardrails and safety protocols to ensure responsible AI deployment.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (PhD preferred).
- Experience: 5+ years of experience building production-grade AI systems, with at least 2 years in a lead or architect role.
- Technical Stack: Proficiency in PyTorch, TensorFlow, or JAX; deep understanding of NLP, transformers, and attention mechanisms.
- Problem Solving: Demonstrated ability to tackle complex, unsolved problems in AI research.
- Communication: Exceptional technical writing and presentation skills, capable of explaining complex concepts to diverse stakeholders.
- Agile Mindset: Experience working in fast-paced, iterative development environments.