Job Description
The Future is Now. At Chronos Dynamics, we are not just keeping pace with technological evolution; we are accelerating it. We are seeking a visionary Senior AI Engineer to lead the development of next-generation Generative Vision Systems. In this role, you will architect the algorithms that define the interaction between humans and machines in the year 2026 and beyond.
Join a world-class team of researchers and engineers dedicated to pushing the boundaries of Artificial General Intelligence (AGI). You will have the autonomy to define technical roadmaps and the resources to build systems that reshape industries.
Why Chronos Dynamics?
- Premium Equity Package: Significant ownership stake in a unicorn startup.
- Remote-First Culture: Work from anywhere, with quarterly global hackathons.
- State-of-the-Art Stack: Access to the latest H100 clusters and proprietary compute infrastructure.
Responsibilities
- Design and implement scalable Large Language Model (LLM) architectures optimized for real-time inference and zero-shot learning capabilities.
- Lead the research and deployment of multimodal generative AI systems, bridging the gap between natural language processing and computer vision.
- Optimize model latency and throughput using distributed training frameworks and quantization techniques.
- Establish best practices for data governance, model explainability, and AI ethics within the engineering department.
- Collaborate with product managers to translate complex AI capabilities into intuitive user experiences.
- Conduct rigorous code reviews and mentor junior engineers to foster a culture of technical excellence.
- Stay ahead of industry trends, evaluating and integrating emerging technologies like Neuromorphic Computing or Quantum AI where applicable.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on Deep Learning, Natural Language Processing, or Computer Vision.
- Minimum of 5 years of professional experience building and deploying production-grade AI models.
- Expert proficiency in Python, PyTorch, and TensorFlow, with experience in Rust or Go for high-performance backend systems.
- Strong understanding of transformer architectures, attention mechanisms, and generative adversarial networks (GANs).
- Proven track record of deploying models at scale on cloud infrastructure (AWS, GCP, or Azure).
- Demonstrated ability to debug complex distributed systems and optimize GPU resource utilization.
- Exceptional communication skills, with the ability to articulate technical concepts to non-technical stakeholders.