Job Description
Are you ready to architect the future?
Chronos Systems is at the forefront of the technological frontier, leading the Project 2026 initiative to revolutionize autonomous decision-making systems. We are looking for a visionary Senior Artificial Intelligence Engineer to join our elite team in San Francisco. In this high-impact role, you will define the architectural standards for next-generation neural networks and drive the development of AI models that will define the landscape of 2026 and beyond.
As a key player in our 2026 roadmap, you will bridge the gap between theoretical research and scalable production systems. If you are passionate about pushing the boundaries of what is possible with Generative AI and Deep Learning, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI models with a focus on ethical and safe deployment.
- Competitive compensation package and equity opportunities.
- Flexible remote-first policy with a vibrant in-office culture in the heart of San Francisco.
Responsibilities
- Architect and deploy scalable Deep Learning models for the Project 2026 initiative, focusing on Large Language Models (LLMs) and Computer Vision.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical AI solutions.
- Optimize existing models for reduced latency and increased inference accuracy to meet 2026 performance benchmarks.
- Mentor junior engineers and conduct code reviews to maintain high technical standards across the AI department.
- Stay ahead of the curve by researching emerging architectures and integrating them into our production pipeline.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, Physics, or a related technical field.
- Minimum of 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
- Proficiency in programming languages such as Python, PyTorch, or TensorFlow.
- Strong experience with distributed computing frameworks (e.g., Apache Spark, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
- Demonstrated experience in deploying AI models to production environments and managing MLOps pipelines.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.