Job Description
Are you ready to architect the future of intelligence? Nexus AI Solutions is seeking a visionary Senior Generative AI Engineer to lead the next generation of Large Language Model (LLM) applications. We are building the infrastructure that powers the next wave of human-machine interaction, and we need a technical expert who thrives on complexity and innovation.
In this role, you will not just write code; you will define the paradigm shift in how machines understand and generate human language. You will work in a collaborative, high-performance environment alongside world-class researchers and engineers.
Why Join Nexus AI?
- Impact at Scale: Work on products used by millions, shaping the ethical and technical landscape of Generative AI.
- Top-Tier Compensation: Competitive salary, equity packages, and comprehensive benefits.
- Cutting-Edge Tech Stack: Access to the latest GPUs, cloud infrastructure, and open-source innovations.
Responsibilities
- Design, train, and fine-tune large-scale generative models (e.g., GPT-4, Llama, Claude) to solve complex business problems.
- Implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Optimize model inference latency and throughput for real-time applications using techniques like quantization and distillation.
- Collaborate with product managers and designers to translate technical capabilities into intuitive user experiences.
- Establish best practices for model deployment, monitoring, and automated retraining loops.
- Conduct research to explore novel architectures and training methodologies.
Qualifications
- Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related technical field.
- Proven experience (5+ years) building and deploying production-grade ML/AI systems.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of Natural Language Processing (NLP) concepts and state-of-the-art transformer architectures.
- Experience with MLOps tools (Docker, Kubernetes, MLflow, Kubeflow) and cloud platforms (AWS, GCP, or Azure).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, ambiguous startup environment.