Job Description
We are pioneering the next generation of intelligent software, and we are seeking a visionary Senior AI Architect to help us define our roadmap for 2026. In this high-impact role, you will not just build AI models; you will architect the foundational systems that will power our enterprise solutions for years to come.
At Nexus Future Systems, we believe in the power of predictive analytics and generative AI to transform industries. You will be responsible for designing scalable, robust, and efficient AI architectures that can handle massive data streams while maintaining real-time latency. This is a unique opportunity to shape the future of technology while working with a team of industry leaders.
Why Join Us?
- Work on cutting-edge projects that define the future of the AI landscape.
- Competitive compensation and equity package.
- Flexible remote-first policy with a hub in the heart of San Francisco.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Design and implement scalable AI/ML architectures specifically tailored for 2026-era performance requirements and scalability.
- Lead the end-to-end lifecycle of machine learning models, from data ingestion and feature engineering to model training, evaluation, and deployment.
- Collaborate with product managers and engineers to integrate AI capabilities seamlessly into our core product ecosystem.
- Optimize existing models for inference speed, accuracy, and cost-efficiency to reduce operational overhead.
- Establish best practices for MLOps, ensuring reproducibility and reliability in production environments.
- Stay ahead of the curve regarding emerging AI trends, such as transformer models, federated learning, and edge AI, and advise the leadership team on their potential applications.
- Mentor a team of talented data scientists and engineers, fostering a culture of technical excellence and innovation.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically focused on AI/ML architecture and system design.
- Deep expertise in Python, TensorFlow, PyTorch, and modern deep learning frameworks.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying large-scale machine learning models into high-traffic production environments.
- Experience with data pipelines (Apache Spark, Kafka) and big data technologies.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Exceptional problem-solving skills and the ability to translate complex business requirements into technical solutions.