Job Description
We are on a mission to define the future of human-machine interaction. Nexus Future Labs is seeking a world-class Generative AI Engineer to architect and deploy cutting-edge Large Language Models (LLMs). If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.
As a key member of our R&D division, you will be responsible for building robust, scalable, and safe AI systems that power our next generation of products. You will work directly with senior researchers to fine-tune models, optimize inference, and integrate AI into complex production environments.
Responsibilities
- Design and implement end-to-end pipelines for training, fine-tuning, and deploying large-scale generative models.
- Optimize model performance for low-latency, high-throughput inference in cloud and edge environments.
- Collaborate with data scientists to curate high-quality datasets and implement RLHF (Reinforcement Learning from Human Feedback).
- Ensure the ethical deployment of AI, focusing on bias mitigation, safety, and interpretability.
- Build and maintain MLOps infrastructure to automate model lifecycle management.
- Stay at the forefront of AI research, evaluating and integrating new techniques from top conferences (NeurIPS, ICML).
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- 5+ years of experience in software engineering, with at least 2 years specifically focused on Machine Learning or Deep Learning.
- Strong proficiency in Python and deep frameworks such as PyTorch or TensorFlow.
- Extensive experience working with Transformer architectures and LLMs (e.g., GPT, Llama, BERT).
- Familiarity with MLOps tools (Kubeflow, MLflow, Seldon) and cloud platforms (AWS, GCP, Azure).
- Experience with vector databases (Pinecone, Weaviate) and RAG architectures.