Job Description
We are pioneering the next generation of intelligent systems for the year 2026 and beyond. Nexus Future Systems is seeking a visionary Senior AI Architect to lead the design and implementation of our cutting-edge Large Language Model (LLM) infrastructure. In this pivotal role, you will define the technical roadmap for our AI products, ensuring scalability, security, and ethical compliance as we shape the future of human-computer interaction.
Join a team of world-class engineers and researchers committed to pushing the boundaries of Artificial General Intelligence (AGI). You will have the autonomy to architect robust systems that power enterprise solutions and consumer applications alike.
Why Join Us?
- Work on projects that define the trajectory of technology for the next decade.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first policy with access to top-tier resources.
- Collaborative environment with leaders in Deep Learning and NLP.
Responsibilities
- Architect and deploy scalable AI/ML infrastructure using Python, PyTorch, and cloud-native technologies.
- Design and fine-tune large language models to meet specific business requirements while ensuring bias mitigation and safety.
- Lead the research and implementation of novel algorithms for Natural Language Processing (NLP) and predictive analytics.
- Collaborate with cross-functional teams to translate complex business problems into elegant technical solutions.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Optimize model inference speed and reduce latency in high-traffic production environments.
- Establish best practices for MLOps, including version control, CI/CD pipelines, and monitoring.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
- Minimum of 7+ years of professional experience in software engineering and machine learning.
- Extensive experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and LLMs (GPT, LLaMA, BERT).
- Strong proficiency in Python and distributed systems design.
- Deep understanding of machine learning theory, including optimization, stochastic gradient descent, and regularization.
- Proven track record of deploying models to production at scale.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.