Job Description
We are building the operating system for the year 2026 and beyond. At Quantum Horizon AI, we are not just predicting the future; we are architecting it. We are seeking a visionary AI/ML Engineer to lead the development of next-generation generative models and autonomous agents.
In this role, you will bridge the gap between theoretical artificial general intelligence (AGI) and practical, scalable enterprise solutions. You will work on cutting-edge projects involving Large Language Models (LLMs), multimodal learning, and ethical AI alignment. If you want to shape the trajectory of technology in the 2026 era, this is your opportunity.
Why Join Us?
- Work on the frontier of AI research and deployment.
- Competitive compensation packages with equity options.
- Flexible remote/hybrid work culture.
- Access to state-of-the-art compute infrastructure.
Responsibilities
- Architect Next-Gen Models: Design, train, and fine-tune large-scale deep learning models to solve complex, ambiguous problems.
- Optimize Performance: Enhance inference speeds and model accuracy through advanced quantization and distributed training techniques.
- Data Strategy: Develop robust data pipelines and curate high-quality training datasets for future-proof models.
- Collaborate Cross-Functionally: Partner with product teams and ethicists to ensure AI systems are safe, transparent, and aligned with human values.
- Roadmap Execution: Translate high-level 2026 strategic goals into actionable technical milestones.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Reinforcement Learning.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed systems.
- Research Mindset: Proven track record of publishing papers or contributing to open-source AI projects.
- Problem Solving: Ability to tackle unstructured problems and derive mathematical models from empirical data.