Job Description
Are you ready to architect the future of intelligent systems? Nexus Future Systems is seeking a visionary Senior AI Architect to lead our next-generation AI initiatives.
As we move toward the technological landscape of 2026, we need a leader who can bridge the gap between theoretical AI research and scalable, production-ready solutions. You will be at the forefront of developing Generative AI, Large Language Models (LLMs), and autonomous systems that redefine human-machine interaction.
Why Join Us?
- Work on cutting-edge projects with global impact.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium San Francisco perks.
Role Overview:
In this high-impact role, you will define the technical roadmap for our AI infrastructure, ensuring our platforms are robust, secure, and scalable for future demands.
Responsibilities
- Architect Scalable AI Solutions: Design and implement robust machine learning pipelines and neural network architectures optimized for high-performance computing.
- Lead Technical Strategy: Define the long-term technical vision for AI integration across product lines, ensuring alignment with business goals.
- Model Optimization: Fine-tune and deploy large-scale models (BERT, GPT, custom transformers) using TensorFlow, PyTorch, and cloud-native infrastructure.
- R&D Leadership: Spearhead research initiatives to explore emerging AI paradigms, including reinforcement learning and computer vision advancements.
- Collaborative Engineering: Partner with software engineers, data scientists, and product managers to deliver seamless user experiences.
- Compliance & Ethics: Establish frameworks for AI governance, ensuring responsible AI development and data privacy compliance.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: Minimum of 7+ years of experience in software engineering, with at least 4 years specializing in AI/ML architecture.
- Technical Skills: Deep expertise in Python, TensorFlow, PyTorch, and experience with MLOps tools (Kubeflow, MLflow).
- Big Data: Proficiency in processing large datasets using Spark, Hadoop, or distributed computing frameworks.
- Cloud Proficiency: Strong experience deploying models on AWS, Azure, or Google Cloud Platform.
- Communication: Exceptional ability to translate complex technical concepts for diverse stakeholders.
- Future-Ready Mindset: Demonstrated ability to adapt to rapid technological shifts and pioneer new methodologies.