Job Description
Are you ready to define the trajectory of the future? 2026 Systems is at the forefront of next-generation predictive intelligence. We are looking for a visionary Senior AI & Predictive Systems Engineer to join our elite engineering team in San Francisco.
In this pivotal role, you will not merely use existing tools; you will help build the infrastructure that defines the technological landscape of the year 2026. You will be responsible for designing and deploying complex neural architectures that power our core predictive platforms, ensuring they are scalable, efficient, and revolutionary.
We offer a competitive compensation package, equity options, and the opportunity to work on projects that genuinely change the world. If you are passionate about the intersection of data science and systems engineering, we want to hear from you.
Responsibilities
- Architect and deploy scalable machine learning pipelines capable of handling high-velocity data streams in real-time.
- Lead the design of cutting-edge neural network architectures, focusing on predictive accuracy and computational efficiency.
- Collaborate closely with product managers and data scientists to translate abstract business requirements into robust, technical solutions.
- Conduct rigorous testing, validation, and performance tuning of AI models to ensure reliability in production environments.
- Drive technical innovation by exploring and integrating emerging research in AI, deep learning, and predictive analytics.
- Mentor junior engineers and foster a culture of continuous learning and technical excellence within the team.
Qualifications
- Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field (PhD is a strong plus).
- 5+ years of professional software development experience, with at least 3 years specializing in AI, Machine Learning, or Predictive Analytics.
- Expert proficiency in Python, C++, and modern deep learning frameworks such as TensorFlow or PyTorch.
- Strong understanding of distributed systems, cloud computing platforms (AWS, Azure, or GCP), and containerization technologies (Docker, Kubernetes).
- Experience with big data technologies (Spark, Kafka) and database management systems.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, agile, and innovative environment.