Job Description
Join the Future at 2026
2026 is pioneering the next generation of autonomous intelligence. We are not just building software; we are architecting the future of human-machine collaboration. We are seeking a visionary Senior AI Architect to lead our core research initiatives and design scalable neural architectures that define the decade ahead.
In this role, you will bridge the gap between theoretical research and production-grade engineering. You will work alongside world-class researchers and engineers to deploy models that impact millions of users globally. If you are passionate about pushing the boundaries of what is possible with Deep Learning and Generative AI, 2026 is the place for you.
Why Join Us?
- Impact: Work on projects that shape the trajectory of the tech industry.
- Compensation: Competitive salary and equity package.
- Environment: Flexible remote-first culture with top-tier equipment.
Responsibilities
- Architectural Leadership: Design and implement scalable AI infrastructure, focusing on latency, throughput, and cost-efficiency for large-scale deployments.
- Model Optimization: Optimize pre-trained models (LLMs, Diffusion, Transformers) for edge devices and cloud environments using techniques like quantization and pruning.
- Research Integration: Translate cutting-edge academic research into practical, production-ready algorithms.
- System Design: Lead the design of distributed training pipelines and data processing systems using modern cloud-native technologies.
- Code Review & Mentorship: Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
- Ethical AI: Ensure deployed models adhere to safety guidelines and ethical AI principles.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of experience in machine learning engineering or applied research, with at least 2 years in a senior leadership role.
- Core Tech Stack: Deep proficiency in Python, PyTorch, and TensorFlow. Experience with distributed computing (Ray, Kubernetes, MPI).
- Cloud Expertise: Proven track record of deploying models on AWS, GCP, or Azure.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with innovative technical solutions.
- Communication: Exceptional ability to communicate complex technical concepts to cross-functional teams.