Job Description
The Future is Now. Build It.
Chronos Tech Solutions is a pioneering organization dedicated to defining the technological landscape of 2026. We are looking for a visionary Senior AI Architect to lead the design and implementation of our next-generation neural infrastructure. If you are passionate about shaping the future of artificial intelligence and possess the technical prowess to build systems that scale, we want to meet you.
In this role, you will be at the forefront of innovation, architecting solutions that bridge the gap between theoretical AI and real-world industrial application. You will work in a high-performance environment focused on ethical AI, large-scale model optimization, and deploying intelligent systems that redefine user experiences.
Why Join Us?
- Work on cutting-edge projects that define the 2026 tech roadmap.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options in the heart of San Francisco.
- Access to state-of-the-art computing infrastructure and research.
Responsibilities
- Design and architect scalable machine learning pipelines and neural network architectures for enterprise-level applications.
- Lead the research and implementation of Large Language Models (LLMs) and generative AI solutions tailored for 2026 market needs.
- Optimize model performance, latency, and throughput for production environments using distributed computing frameworks.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical AI solutions.
- Establish best practices for model deployment, monitoring, and MLOps to ensure system reliability and ethical AI compliance.
- Stay ahead of industry trends in AI, quantum computing integration, and edge AI to drive innovation.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field (or equivalent extensive professional experience).
- Minimum of 7+ years of experience in software engineering and machine learning architecture.
- Deep proficiency in Python, C++, and at least one major deep learning framework (PyTorch, TensorFlow, or JAX).
- Proven experience designing and deploying large-scale transformer models and NLP systems.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Experience with MLOps tools such as MLflow, Kubeflow, or AWS SageMaker.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.