Job Description
Welcome to Nexus Future Systems, where we are defining the technological landscape of 2026 and beyond. We are seeking a visionary Senior AI Engineer to join our elite team in Austin, Texas. In this pivotal role, you will spearhead the development of cutting-edge Generative AI models, Large Language Models (LLMs), and autonomous systems.
Our mission is to build the intelligence layer of the future. You will work directly with our Principal Engineers to architect scalable AI solutions that power our enterprise clients. If you are passionate about pushing the boundaries of machine learning and want to be at the forefront of the AI revolution, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware and software stacks.
- Competitive compensation package including equity.
- Flexible remote and hybrid work options.
- Professional development and learning stipends.
Responsibilities
- Model Development: Design, train, and deploy advanced machine learning and deep learning models, specifically focusing on Generative AI and NLP.
- Infrastructure Optimization: Optimize model inference performance and reduce latency in high-throughput environments using techniques like quantization and distillation.
- Research: Stay at the forefront of AI research, implementing novel algorithms and integrating them into our production pipeline.
- Collaboration: Partner with data scientists, software engineers, and product managers to translate business requirements into technical AI solutions.
- Code Review: Mentor junior engineers and conduct rigorous code reviews to ensure code quality, scalability, and best practices.
- MLOps: Implement and maintain CI/CD pipelines for machine learning models using modern MLOps tools.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years focused on Generative AI or LLMs.
- Programming: Strong proficiency in Python, PyTorch, and TensorFlow.
- Algorithms: Deep understanding of statistical learning, neural networks, and optimization algorithms.
- Cloud: Experience deploying models on cloud platforms such as AWS, GCP, or Azure.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.