Job Description
Are you ready to define the future of Artificial Intelligence? Chronos Future Labs is seeking a visionary Senior AI Architect to lead our cutting-edge research initiatives targeting the 2026 technology landscape. In this pivotal role, you will architect scalable, next-generation machine learning systems that redefine user interaction and automation.
We are looking for a thought leader who doesn't just implement existing models but designs the infrastructure for the next decade. You will work directly with our CTO and a world-class team of data scientists to bridge the gap between theoretical AI capabilities and real-world enterprise applications.
Why Join Us?
• Work on groundbreaking projects that will shape the 2026 tech ecosystem.
• Competitive compensation and equity package.
• Flexible remote-first policy with a hub in San Francisco.
Responsibilities
- Architect Future-Proof Systems: Design and deploy robust machine learning pipelines and neural network architectures optimized for the demands of 2026 and beyond.
- Lead Model Innovation: Spearhead the research and implementation of Generative AI, Large Language Models (LLMs), and predictive analytics tools.
- Optimize Performance: Enhance model accuracy, reduce latency, and ensure high scalability across distributed cloud environments.
- Collaborate Across Teams: Partner with product managers and software engineers to translate complex AI requirements into actionable technical specifications.
- Establish Best Practices: Create and maintain technical documentation, coding standards, and MLOps workflows to ensure reproducibility and efficiency.
- Future-Proofing Strategy: Conduct feasibility studies for emerging AI technologies to inform the company's 2026 strategic roadmap.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, Physics, or a related field (PhD preferred).
- Experience: Minimum of 5-7 years of experience in AI, Machine Learning, or Deep Learning engineering roles.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Docker, Kubernetes, MLflow).
- Specialization: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Expertise: Demonstrated ability to architect solutions on major cloud providers (AWS, GCP, or Azure).
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical concepts to non-technical stakeholders.