Job Description
QuantumHorizon Inc. is pioneering the next generation of intelligent systems as we look toward the technological landscape of 2026. We are seeking a visionary Senior AI Engineer to lead our research and development efforts in Generative AI and Large Language Models (LLMs). In this pivotal role, you will architect scalable AI solutions that redefine user experiences and drive business innovation.
As a key member of our technical team, you will bridge the gap between cutting-edge research and production-grade software. You will be responsible for designing, training, and deploying state-of-the-art neural networks, ensuring our models are not only powerful but also efficient and responsible.
Why Join Us?
- Work on mission-critical AI infrastructure that shapes the future.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with a focus on work-life balance.
Responsibilities
- Model Architecture: Design and implement advanced neural network architectures, specifically focusing on Transformers, GPT models, and RAG (Retrieval-Augmented Generation) systems.
- Research & Development: Stay ahead of the curve by researching the latest papers in NLP and Deep Learning, adapting novel techniques for our specific use cases.
- Production Deployment: Optimize model inference latency and throughput to ensure seamless integration into our cloud-native microservices architecture.
- Collaboration: Partner with data scientists, product managers, and engineers to translate complex AI requirements into robust, scalable software products.
- MLOps: Establish best practices for MLOps pipelines, including version control, model monitoring, and automated retraining workflows.
Qualifications
- Education: Master’s or Ph.D. degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: Minimum of 5 years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow; strong understanding of distributed computing (Spark, Ray) and GPU optimization (CUDA).
- Frameworks: Proven experience with Hugging Face, LangChain, or similar frameworks for model fine-tuning and application development.
- Problem Solving: Demonstrated ability to troubleshoot complex technical challenges and optimize performance in high-volume environments.