Job Description
Are you ready to architect the technology stack for the year 2026? Horizon Dynamics is a forward-thinking pioneer in next-generation generative intelligence. We are looking for a visionary Senior AI Engineer to lead our core research and development efforts. If you thrive on pushing the boundaries of what's possible with Large Language Models (LLMs) and autonomous agents, this is your opportunity to define the future of enterprise automation.
Why Join Us?
At Horizon Dynamics, we don't just predict the future; we build it. You will work with a world-class team of researchers and engineers to deploy cutting-edge AI solutions that solve complex real-world problems. We offer a competitive salary, equity packages, and a culture that prioritizes innovation and intellectual freedom.
Responsibilities
- Lead Model Development: Design, train, and fine-tune proprietary Large Language Models (LLMs) and transformer architectures for high-impact applications.
- System Architecture: Build scalable, high-performance machine learning pipelines and inference engines capable of handling millions of requests per second.
- MLOps Implementation: Establish robust CI/CD workflows for machine learning, ensuring seamless deployment, monitoring, and retraining cycles.
- Research & Innovation: Stay at the forefront of AI research, experimenting with novel techniques in reinforcement learning, multimodal learning, and edge AI.
- Collaboration: Partner with product managers and software engineers to translate technical AI capabilities into user-centric product features.
- Performance Optimization: Rigorously optimize model latency and resource efficiency to ensure sub-millisecond response times in production environments.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years specifically in LLM development or NLP.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow. Deep understanding of neural network architectures.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Strong analytical skills with the ability to debug complex distributed systems and optimize algorithmic performance.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.