Job Description
We are on a mission to architect the future of intelligence for 2026. Nexus Horizon is seeking a visionary Senior AI Engineer to lead the development of our proprietary Large Language Models (LLMs) and multimodal AI systems. If you are passionate about pushing the boundaries of what is possible in generative AI and want to build the foundation for the next decade of human-machine interaction, we want to hear from you.
In this role, you will work closely with our research scientists and product teams to deploy state-of-the-art models that solve complex enterprise challenges. You will be at the forefront of the 2026 AI revolution, optimizing performance, scalability, and ethical AI usage.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art LLMs (e.g., GPT-4 architecture) to achieve superior performance benchmarks for enterprise use cases.
- RAG Architecture: Build and optimize Retrieval-Augmented Generation pipelines to ensure factual accuracy and reduce hallucinations in AI outputs.
- Infrastructure Optimization: Deploy models on scalable cloud infrastructure (AWS/Azure/GCP) utilizing Kubernetes and containerization for high availability.
- Prompt Engineering: Develop advanced prompting strategies and guardrails to enhance model safety, security, and compliance with industry regulations.
- Performance Tuning: Conduct rigorous A/B testing and latency analysis to ensure real-time inference capabilities.
- Cross-Functional Leadership: Mentor junior engineers and collaborate with product managers to translate technical requirements into scalable AI solutions.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, specifically with Deep Learning frameworks (PyTorch, TensorFlow, JAX).
- Core Skills: Proficiency in Python, SQL, and experience with GPU acceleration (CUDA, NVIDIA).
- System Design: Strong understanding of distributed systems, MLOps pipelines, and cloud-native architecture.
- Language: Native or professional proficiency in English.
- Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.