Job Description
Join the Frontier of Intelligence. We are building the foundational AI architectures for the year 2026. As a Senior AI Engineer at Apex Horizon, you won't just be maintaining existing models; you will be architecting the neural networks that will define the next decade of human-machine interaction.
The Role:
You will lead the research and deployment of cutting-edge Large Language Models (LLMs) and multimodal AI systems. You will bridge the gap between theoretical research and scalable production engineering, ensuring our AI solutions are not only powerful but also safe, efficient, and ethical. If you are passionate about pushing the boundaries of what is possible in Generative AI, we want to hear from you.
Why Join Us?
- Work on projects that are shaping the future of the tech landscape.
- Competitive compensation and equity packages.
- Access to state-of-the-art hardware and cloud resources.
Responsibilities
- Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) and Transformer architectures.
- Optimize model inference latency and reduce token generation costs for real-time applications.
- Implement advanced Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and hallucination reduction.
- Collaborate with cross-functional teams of data scientists, product managers, and security experts to ensure AI safety and compliance.
- Publish research findings and contribute to open-source initiatives within the AI community.
- Conduct rigorous A/B testing and model evaluation to drive continuous improvement.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years focused on Large Language Models or Generative AI.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of deep learning principles, neural network architectures, and optimization techniques.
- Experience deploying models at scale using cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker/Kubernetes).
- Strong background in NLP, Natural Language Understanding (NLU), and Natural Language Generation (NLG).