Job Description
Shape the Future. Architect the Impossible.
Nexus Future Labs is pioneering the next generation of sentient computing with Project 2026. We are looking for a visionary Lead AI Architect to design the neural frameworks that will define the era of 2026 and beyond. If you are obsessed with pushing the boundaries of Machine Learning, Ethical AI, and Human-Computer Interaction, this is your mission.
In this role, you will lead a world-class team of researchers and engineers, bridging the gap between theoretical AI breakthroughs and scalable, real-world applications. You won't just write code; you will define the architectural DNA of the future.
Why Nexus Future Labs?
- Work on mission-critical projects that redefine industry standards.
- Competitive compensation package with performance-based bonuses.
- Top-tier benefits including unlimited PTO, health, and dental coverage.
- Access to the latest hardware and research facilities.
Responsibilities
- Architectural Leadership: Design and implement the core neural network architectures for Project 2026, ensuring scalability, efficiency, and robustness.
- R&D Strategy: Identify and evaluate emerging AI technologies (e.g., Neuromorphic Computing, Generative Adversarial Networks) to integrate into our roadmap.
- Team Mentorship: Mentor junior and senior engineers, conducting code reviews, technical architecture sessions, and fostering a culture of innovation.
- Model Optimization: Oversee the optimization of large language models and reinforcement learning agents to improve inference speed and accuracy.
- Ethical AI Governance: Establish and enforce guidelines for responsible AI development, ensuring fairness, transparency, and bias mitigation in all models.
- Stakeholder Communication: Translate complex technical concepts into compelling narratives for investors, stakeholders, and executive leadership.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
- Experience: 8+ years of professional experience in AI/ML engineering, with at least 3 years in a lead or architect role.
- Technical Stack: Proficiency in Python, C++, and frameworks such as TensorFlow, PyTorch, or JAX. Experience with distributed systems (Kubernetes, Docker) is highly preferred.
- Domain Knowledge: Deep understanding of Deep Learning, Natural Language Processing (NLP), or Computer Vision.
- Problem Solving: Proven track record of solving complex, unstructured problems in high-pressure environments.
- Creativity: A passion for exploring the unknown and the ability to think beyond current industry constraints.