Job Description
Are you ready to define the technological landscape of 2026? Nexus Future Labs is seeking a visionary Senior Generative AI Engineer to lead our next generation of artificial intelligence initiatives. We are not just building models; we are architecting the future of human-machine interaction. If you possess a deep understanding of Large Language Models (LLMs) and a passion for ethical AI, we want to hear from you.
In this pivotal role, you will be at the forefront of innovation, bridging the gap between theoretical research and scalable production systems. You will work with a world-class team of researchers, engineers, and product designers to deploy cutting-edge AI solutions that solve complex real-world problems. Join us in shaping the roadmap for 2026 and beyond.
Responsibilities
- Architect & Develop: Design, train, and fine-tune large-scale generative models using state-of-the-art frameworks (PyTorch, TensorFlow, JAX).
- RAG Implementation: Build robust Retrieval-Augmented Generation pipelines to enhance model accuracy and reduce hallucinations.
- Optimization: Optimize model inference speeds and resource efficiency for cloud and edge deployment environments.
- Ethical AI: Implement fairness, accountability, and transparency (FAIR) principles into all AI model training and deployment cycles.
- Research: Stay abreast of the latest academic papers and industry trends to integrate novel techniques into our product suite.
- Collaboration: Partner with product managers and stakeholders to translate technical requirements into actionable development roadmaps.
- Code Review: Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, C++, and SQL. Strong experience with Hugging Face Transformers, LangChain, and vector databases (Pinecone, Milvus).
- Modeling: Proven track record of fine-tuning pre-trained models (e.g., GPT-4, Llama 3, Claude) for specific business applications.
- Deployment: Experience deploying models to production using Kubernetes, Docker, and cloud infrastructure (AWS, GCP, or Azure).
- Communication: Excellent written and verbal communication skills with the ability to explain complex technical concepts to non-technical audiences.
- Problem Solving: Exceptional analytical and problem-solving skills with a focus on system architecture.