Job Description
We are on the precipice of a technological paradigm shift. Nexus Future Labs is seeking a visionary Lead AI Architect to define the architecture of our generative AI platforms for the 2026 era. In this role, you will not just build models; you will engineer the intelligence that powers autonomous agents and multimodal systems of tomorrow.
You will be at the helm of our Research & Engineering division, bridging the gap between cutting-edge theoretical research and scalable, production-grade infrastructure. If you are passionate about ethical AI, large-scale distributed systems, and pushing the boundaries of what is possible, we want to hear from you.
What You'll Do:
- Architect and deploy scalable ML pipelines using Python, Rust, and distributed computing frameworks.
- Lead research initiatives into Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Optimize transformer models for low-latency, high-throughput inference at scale.
- Establish best practices for AI safety, bias mitigation, and model explainability.
- Collaborate with product stakeholders to translate complex AI capabilities into intuitive user features.
- Mentor a world-class team of researchers and engineers, fostering a culture of innovation and technical excellence.
Responsibilities
- Architect and deploy scalable ML pipelines using Python, Rust, and distributed computing frameworks.
- Lead research initiatives into Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Optimize transformer models for low-latency, high-throughput inference at scale.
- Establish best practices for AI safety, bias mitigation, and model explainability.
- Collaborate with product stakeholders to translate complex AI capabilities into intuitive user features.
- Mentor a world-class team of researchers and engineers, fostering a culture of innovation and technical excellence.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of experience building production-grade AI systems and deploying LLMs.
- Deep expertise in PyTorch, TensorFlow, or JAX.
- Proven track record in Generative AI, NLP, and multimodal model training.
- Strong background in System Design and cloud architecture (AWS/GCP/Azure).
- Excellent communication skills to articulate complex technical concepts to non-technical stakeholders.