Job Description
We are Nexus Future Systems, a pioneer in next-generation predictive intelligence. As we approach the pivotal year of 2026, we are seeking a visionary Senior AI/ML Engineer to architect the algorithms that will define the future of human-computer interaction. This is not just a job; it is a mission to build the infrastructure for the year 2026 and beyond.
In this role, you will be at the forefront of Generative AI, Large Language Models (LLMs), and autonomous decision-making systems. You will work alongside world-class researchers and engineers to solve complex problems at the intersection of neural networks, distributed computing, and real-time data streams.
Why Join Us?
- Shape the roadmap for 2026.
- Work with state-of-the-art tech stack.
- Competitive equity and benefits.
If you are passionate about the future of technology and want to leave a lasting impact, we want to hear from you.
Responsibilities
- Architect and deploy scalable machine learning models tailored for the 2026 infrastructure ecosystem.
- Lead the development of next-generation NLP pipelines, focusing on agentic AI and multi-modal reasoning.
- Optimize model inference latency and reduce computational costs for high-throughput environments.
- Collaborate with cross-functional teams to translate 2026 strategic vision into technical specifications.
- Maintain and improve our MLOps pipeline, ensuring reproducibility and CI/CD best practices.
- Conduct rigorous research and experimentation to stay ahead of emerging AI paradigms.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in building and deploying ML systems in production.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Proven track record of working with LLMs, Transformers, or reinforcement learning.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Strong understanding of data structures, algorithms, and software engineering principles.