Job Description
We are at the precipice of a technological singularity. At Nexus Future Labs, we aren't just predicting the future; we are engineering it. As we gear up for our 2026 Horizon initiative, we are seeking a visionary Senior AI Research Engineer to lead the development of next-generation Artificial General Intelligence (AGI) systems.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, real-world applications. You will work with a world-class team of data scientists, cryptographers, and quantum computing experts to build the intelligence layer of the Nexus ecosystem.
Why Join Us?
- Impact: Your work will directly define the trajectory of human-machine interaction.
- Innovation: Access to cutting-edge hardware and proprietary datasets.
- Growth: A transparent career path with equity opportunities in a unicorn startup.
Ready to build the future? Apply today.
Responsibilities
- Lead Research Initiatives: Spearhead the design and implementation of novel neural architectures targeting AGI capabilities.
- Prototype Development: Build and iterate on proof-of-concept models in Python and C++ that push the boundaries of current LLM and Transformer technology.
- Model Optimization: Apply advanced quantization, pruning, and distillation techniques to deploy massive models on edge devices.
- Team Mentorship: Mentor junior researchers and engineers, fostering a culture of scientific curiosity and technical excellence.
- Publication & Collaboration: Author high-impact research papers for top-tier conferences (NeurIPS, ICML) and collaborate with academic institutions.
- Risk Mitigation: Identify and address ethical biases and safety concerns in autonomous systems.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- Experience: 5+ years of experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Apache Spark, Ray).
- Domain Knowledge: Deep understanding of Transformer models, reinforcement learning, and large-scale training pipelines.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to diverse stakeholders.
- Passion: A demonstrated passion for the future of AI and the ethical implications of advanced technology.