Job Description
We are not just building software; we are architecting the intelligence infrastructure of the year 2026. Apex Future Labs is seeking a visionary Next-Gen AI Architect to lead the development of our proprietary Large Language Models (LLMs) and autonomous agent systems.
In this high-impact role, you will bridge the gap between cutting-edge theoretical research and production-grade engineering. You will define the technical roadmap for our AI ecosystem, ensuring scalability, safety, and unprecedented performance. If you are passionate about the future of Artificial General Intelligence and want to shape the digital landscape of tomorrow, this is your opportunity.
Why Join Us?
We offer competitive equity packages, flexible remote-first policies, and the chance to work on projects that define the next decade of technology.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable, high-performance neural network architectures optimized for real-time inference and training efficiency.
- Lead Research Implementation: Translate advanced academic research into robust, production-ready code, focusing on Generative AI, reinforcement learning, and multimodal learning.
- Model Optimization: Drive initiatives to reduce latency and cost, utilizing techniques such as quantization, distillation, and edge-computing deployment.
- Technical Mentorship: Foster a culture of innovation by mentoring junior engineers and conducting code reviews that push technical boundaries.
- Strategic Roadmapping: Collaborate with product and executive leadership to align AI capabilities with business goals and future market trends.
- Ethical AI Governance: Implement safety guidelines and bias mitigation strategies to ensure responsible AI deployment.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Core Expertise: Deep proficiency in Python, C++, and modern ML frameworks (PyTorch, TensorFlow, JAX).
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a lead or architect role.
- System Design: Proven track record of designing large-scale distributed systems and managing complex model lifecycles.
- Language Mastery: Strong understanding of NLP, Computer Vision, or Reinforcement Learning algorithms.
- Problem Solving: Exceptional ability to troubleshoot complex performance bottlenecks and optimize computational efficiency.