Job Description
Are you ready to define the future of intelligence? Chronos AI Systems is pioneering the next generation of artificial intelligence, and we are looking for visionary minds to join our elite R&D team. As a Senior AI Research Engineer, you will play a pivotal role in architecting scalable neural networks and deploying breakthrough models that will redefine human-machine interaction by 2026.
At Chronos, we don't just predict the future; we build it. Our mission is to create ethical, robust, and efficient AI systems that solve the world's most complex challenges. If you are passionate about pushing the boundaries of deep learning, computer vision, or natural language processing, this is your opportunity to lead from the front.
Why Join Us?
- Work with state-of-the-art hardware (NVIDIA H100 clusters, TPUs).
- Competitive equity package and comprehensive benefits.
- Flexible remote-first policy with a hub in the heart of SF.
- Access to a world-class library and collaboration with top-tier researchers.
Responsibilities
- Research & Development: Design, implement, and optimize state-of-the-art deep learning algorithms to meet the rigorous demands of our 2026 roadmap.
- Model Training: Lead the end-to-end training lifecycle of large-scale models, including data preprocessing, fine-tuning, and validation.
- System Architecture: Collaborate with MLOps engineers to ensure seamless deployment, monitoring, and scaling of models in production environments.
- Innovation: Publish high-impact research papers and contribute to open-source initiatives to establish Chronos as a thought leader in the AI space.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML research or engineering, with a proven track record of publications or production deployments.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of transformer architectures, reinforcement learning, or generative models.
- Problem Solving: Exceptional ability to tackle ambiguous problems and derive data-driven solutions.
- Communication: Strong written and verbal communication skills, capable of translating complex technical concepts for diverse audiences.