Job Description
At 2026 Systems, we are pioneering the technological frontier. Our mission is to define the digital landscape of the coming decade by developing next-generation artificial intelligence systems that redefine human-machine interaction. We are seeking a visionary Senior AI Architect to lead our research division and bridge the gap between theoretical innovation and scalable production deployment.
As a key member of our elite engineering team, you will be responsible for architecting the core models that power our flagship products. You will work in a high-performance, collaborative environment that prioritizes technical excellence, creative problem-solving, and rapid iteration.
Why Join Us?
• Work on cutting-edge generative AI and autonomous systems.
• Competitive compensation and equity packages.
• Top-tier equipment and remote-first flexibility.
• Direct impact on the roadmap for the year 2026 and beyond.
Responsibilities
- Architectural Leadership: Design and implement scalable, distributed machine learning infrastructure capable of handling petabyte-scale data processing.
- Research & Development: Lead research initiatives focused on Large Language Models (LLMs), reinforcement learning, and multi-modal AI systems.
- Model Optimization: Fine-tune and optimize pre-trained models for inference speed, latency, and memory efficiency on edge devices.
- Technical Mentorship: Guide a team of junior data scientists and ML engineers, fostering a culture of continuous learning and technical rigor.
- Production Deployment: Collaborate with DevOps and software engineering teams to ensure seamless integration of AI models into production environments.
- Roadmap Strategy: Contribute to the strategic planning of technical roadmaps, identifying emerging technologies that align with our 2026 vision.
Qualifications
- Education: Master’s or Ph.D. degree in Computer Science, Mathematics, Physics, or a related quantitative field.
- Experience: Minimum of 5-8 years of professional experience in machine learning research and software engineering.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and C++. Deep experience with distributed computing frameworks (e.g., Kubernetes, Ray, Spark).
- Model Expertise: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-stakes environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.