Job Description
Are you ready to define the landscape of artificial intelligence for 2026 and beyond?
Quantum Horizon is pioneering the next generation of autonomous agents and generative AI systems. We are seeking a visionary Senior AI/ML Engineer to join our elite research division and architect the algorithms that will power the future web.
In this high-impact role, you won't just maintain existing models; you will build the infrastructure for the AI evolution of 2026. You will work at the intersection of deep learning, large language models (LLMs), and scalable distributed systems. If you are passionate about pushing the boundaries of what is possible in AI and want to leave a lasting mark on the industry, we want to hear from you.
Why Join Us?
- Future-Forward Vision: Directly contribute to the strategic roadmap for our 2026 AI suite.
- Top-Tier Compensation: Competitive salary plus equity in a high-growth unicorn.
- Cutting-Edge Stack: Work with the latest in PyTorch, TensorFlow, and proprietary cloud infrastructure.
Key Responsibilities:
Responsibilities
- Architect and train state-of-the-art Large Language Models (LLMs) and multimodal systems optimized for enterprise deployment.
- Design and implement robust MLOps pipelines to ensure scalability, monitoring, and retraining of models in production environments.
- Lead research initiatives exploring novel architectures for AI Agents and autonomous decision-making systems.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate complex AI concepts into user-centric features.
- Optimize model inference latency and reduce computational costs for large-scale deployments.
- Conduct rigorous experimentation and A/B testing to validate model performance and drive continuous improvement.
Qualifications:
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on Machine Learning.
- Proven experience (5+ years) building, training, and deploying production-grade machine learning models.
- Expert proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Strong understanding of natural language processing (NLP) techniques and transformer architectures.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical ideas to non-technical stakeholders.
Skills: Python, PyTorch, TensorFlow, NLP, MLOps, Machine Learning, Deep Learning, SQL, Cloud Computing