Job Description
Are you ready to architect the next generation of intelligent applications? Nexus Future Tech is seeking a visionary Senior Generative AI Engineer to join our elite engineering team. We are at the forefront of the AI revolution, developing scalable Large Language Models (LLMs) and cutting-edge multimodal systems that define the future of human-computer interaction.
In this role, you will bridge the gap between theoretical research and production-grade deployment. You will optimize transformer architectures, fine-tune proprietary models, and ensure our AI solutions are not only powerful but also ethical and efficient. If you are passionate about the intersection of deep learning and real-world impact, we want to hear from you.
Why Join Us?
We offer a competitive compensation package, equity options, and the opportunity to work with industry pioneers in a fully remote-first culture that values innovation and autonomy.
Responsibilities
- Model Development & Optimization: Design, train, and fine-tune large-scale generative models (GPT, LLaMA, Claude architectures) using PyTorch and TensorFlow.
- System Architecture: Build robust MLOps pipelines for model training, validation, and deployment on cloud infrastructure (AWS/GCP/Azure).
- Performance Tuning: Implement quantization, pruning, and distributed training strategies to reduce latency and increase inference throughput.
- Code Review & Mentorship: Lead technical discussions, conduct code reviews, and mentor junior engineers and data scientists.
- RAG Implementation: Develop and optimize Retrieval-Augmented Generation systems to enhance model accuracy and reduce hallucinations.
Qualifications
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Proficiency in Python, C++, and modern deep learning frameworks (PyTorch, JAX, or TensorFlow).
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related technical field.
- Cloud Expertise: Strong experience deploying models on cloud platforms (AWS SageMaker, Google AI Platform).
- Problem Solving: Demonstrated ability to solve complex optimization problems in high-concurrency environments.