Job Description
Shape the Future of Intelligence at Nexus Horizon
We are pioneering the next generation of artificial intelligence solutions, and we are looking for a visionary Senior AI Engineer to join our elite research and engineering team. If you are passionate about Large Language Models (LLMs), Generative AI, and pushing the boundaries of what's possible in 2026, this is your opportunity to lead high-impact projects.
In this role, you will architect and deploy scalable AI systems that power our enterprise clients. You will work at the intersection of deep learning, MLOps, and product engineering to build safe, efficient, and ground-breaking AI products.
Why Join Us?
- State-of-the-Art Stack: Work with the latest in Transformers, Vector Databases, and GPU acceleration.
- Impactful Work: Your code will directly influence how millions of users interact with AI.
- Competitive Compensation: Top-tier salary, comprehensive benefits, and equity packages.
- Flexible Culture: Embrace a remote-first culture with a focus on autonomy and results.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale foundation models and LLMs using PyTorch and TensorFlow.
- System Architecture: Build robust and scalable MLOps pipelines for training, evaluation, and deployment of AI models.
- RAG Implementation: Develop and optimize Retrieval-Augmented Generation systems to enhance model accuracy and reduce hallucinations.
- Performance Optimization: Conduct rigorous performance benchmarking and optimize inference latency and throughput.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineers to define AI product requirements and roadmaps.
- Research & Innovation: Stay ahead of the curve by integrating cutting-edge research (e.g., MoE, quantization, RAG) into production systems.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field. PhD preferred.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Programming: Expert proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow, JAX).
- NLP Expertise: Strong understanding of NLP concepts, tokenization, embeddings, and transformer architectures.
- MLOps: Experience with cloud platforms (AWS/GCP/Azure), containerization (Docker), and orchestration (Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex algorithmic problems and deliver production-grade solutions.