Job Description
Are you ready to architect the next generation of intelligent systems? Nexus Future Labs is seeking a visionary Senior Generative AI Engineer to lead our breakthrough initiatives in Large Language Models (LLMs) and Autonomous Agents.
As we prepare for the AI evolution of 2026, we are looking for a technical leader who thrives at the intersection of research and production engineering. You will be responsible for building the core infrastructure that powers our next-gen SaaS platforms, ensuring scalability, safety, and performance in real-world scenarios.
Why Join Us?
- Work on cutting-edge AI models that will define the future.
- Competitive salary and equity package.
- Remote-first culture with flexible hours.
- Access to the latest hardware for training and inference.
Don't just keep up with the future—shape it.
Responsibilities
- Design, train, and fine-tune proprietary Large Language Models using transformer architectures.
- Implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Optimize model inference performance for low-latency, high-throughput production environments.
- Collaborate with cross-functional teams (Product, Design, Data Science) to translate business requirements into technical AI solutions.
- Establish and enforce best practices for AI ethics, safety, and compliance in model deployment.
- Conduct research to explore emerging architectures and methodologies in the Generative AI space.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in software engineering and machine learning, with at least 2 years specifically in Generative AI or NLP.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Strong experience with Hugging Face Transformers, LangChain, or similar model orchestration frameworks.
- Experience deploying models to cloud environments (AWS, GCP, or Azure) using Docker and Kubernetes.
- Proven track record of improving model performance metrics (BLEU, ROUGE, or custom LLM benchmarks).
- Excellent communication skills and ability to explain complex technical concepts to non-technical stakeholders.