Job Description
The Future is Now. Nexus Future Labs is pioneering the next generation of intelligent systems. We are looking for a visionary Senior AI Engineer (2026 Tech Vision) to lead the development of cutting-edge Generative AI and Machine Learning solutions that will define the industry standard for the mid-2020s.
In this role, you will not just build models; you will architect the infrastructure that powers the future of human-computer interaction. You will work with state-of-the-art Large Language Models (LLMs), multimodal AI, and autonomous agents.
Why Join Us?
- Work on projects that have a tangible impact on global industries.
- Competitive compensation package with equity options.
- Top-tier equipment and a culture of continuous innovation.
If you are passionate about pushing the boundaries of what AI can achieve, we want to hear from you.
Responsibilities
- Model Architecture: Design, train, and fine-tune large-scale generative models (e.g., GPT, Llama, Claude variants) using PyTorch and TensorFlow.
- System Optimization: Implement advanced inference optimization techniques to reduce latency and cost while maximizing throughput.
- RAG & Integration: Develop and deploy Retrieval-Augmented Generation (RAG) architectures to enhance model accuracy and reduce hallucinations.
- MLOps Pipeline: Build scalable CI/CD pipelines for machine learning models using Kubeflow or MLflow.
- Research & Development: Stay ahead of the curve by researching emerging architectures and integrating novel techniques into production environments.
- Mentorship: Lead a team of junior data scientists and engineers, conducting code reviews and technical workshops.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning Engineering or Applied AI.
- Programming: Deep expertise in Python and experience with GPU acceleration (CUDA, Numba).
- Frameworks: Proficiency in PyTorch or JAX; experience with Hugging Face Transformers and LangChain.
- Mathematics: Strong foundation in Linear Algebra, Calculus, and Probability Statistics.
- Soft Skills: Excellent problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.