Job Description
Are you ready to architect the future?
Apex Future Systems is at the forefront of the Project 2026 initiative, a groundbreaking effort to redefine the boundaries of artificial general intelligence and next-gen automation. We are looking for a visionary Senior AI Engineer to join our elite San Francisco team and build the systems that will power the enterprise of tomorrow.
In this role, you won't just maintain existing codebases; you will pioneer new paradigms in deep learning, distributed systems, and predictive analytics. We value bold thinking, technical excellence, and the ability to translate complex theoretical models into scalable, real-world solutions.
Why join Project 2026?
- Work on cutting-edge AI infrastructure that will shape the industry for the next decade.
- Competitive compensation package with equity opportunities.
- Flexible work environment in the heart of the tech hub.
Responsibilities
- Architect and Deploy: Design and implement high-scale, low-latency machine learning pipelines capable of processing billions of data points in real-time.
- Model Innovation: Lead the research and development of novel neural architectures, specifically focusing on Transformer models and reinforcement learning applications.
- System Optimization: Continuously monitor, tune, and optimize model performance to ensure maximum throughput and accuracy in production environments.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and software engineers to define technical roadmaps and deliver product excellence.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of knowledge sharing and technical growth within the team.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 5+ years of professional experience in building and deploying ML systems in a production environment.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Apache Spark, Kubernetes).
- Domain Knowledge: Strong understanding of Natural Language Processing (NLP), Computer Vision, or Large Language Models (LLMs).
- Problem Solving: Demonstrated ability to tackle ambiguous problems and devise elegant, scalable engineering solutions.