Job Description
We are seeking a visionary Senior AI Engineer to join our elite team at Nexus Horizon. As we architect the infrastructure for the AI evolution of 2026, you will be at the forefront of building autonomous agents, generative systems, and adaptive learning models. This is not just a job; it is an opportunity to define the future of human-machine interaction.
In this high-impact role, you will bridge the gap between cutting-edge research and production-grade deployment. You will lead the charge in developing scalable, secure, and efficient AI solutions that power our next generation of products. If you are passionate about pushing the boundaries of what is possible in Artificial Intelligence and want to work in a culture of innovation, we want to meet you.
Why Join Us?
- Work with state-of-the-art Large Language Models (LLMs) and Agentic workflows.
- Competitive equity package and top-tier compensation.
- Flexible remote-first culture with a focus on output over hours.
Responsibilities
- Architect AI Solutions: Design, develop, and deploy advanced machine learning models and agentic AI systems that align with the 2026 technology roadmap.
- Optimization & Scaling: Optimize inference pipelines and reduce latency for real-time AI applications serving millions of users.
- Research Implementation: Translate theoretical research papers into production-ready code using PyTorch, TensorFlow, or similar frameworks.
- MLOps Leadership: Build and maintain CI/CD pipelines for machine learning, ensuring model reproducibility and governance.
- Cross-Functional Collaboration: Partner with product managers and data scientists to define technical requirements and deliver high-quality features.
- RAG & Vector DBs: Spearhead the development of Retrieval-Augmented Generation systems to enhance model accuracy and context awareness.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years focused on Machine Learning or Deep Learning.
- Technical Stack: Proficiency in Python, C++, and SQL. Strong experience with PyTorch, Hugging Face Transformers, and LangChain.
- Modeling: Deep understanding of Neural Networks, Transformers, and fine-tuning large language models.
- Deployment: Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Docker and Kubernetes.
- Problem Solving: Proven track record of solving complex technical challenges and improving model performance metrics.