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Senior AI Engineer (2026 Roadmap)

Apex Neural Systems
San Francisco
Estimated Salary
USD 165.000 – USD 235.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Are you ready to architect the future of Artificial Intelligence? Apex Neural Systems is seeking a visionary Senior AI Engineer to lead our 2026 roadmap initiatives. We are building the next generation of autonomous agents and generative models, and we need a technical leader who can bridge the gap between theoretical breakthroughs and production-grade scalability.

In this role, you will define the technical strategy for our flagship product, ensuring our models are not only state-of-the-art but also ethically aligned and highly performant. If you thrive in a fast-paced, innovative environment and want to leave a lasting legacy in the AI space, we want to hear from you.

Responsibilities

  • Architect & Scale: Design and deploy large-scale machine learning infrastructure capable of processing billions of data points with sub-millisecond latency.
  • Model Development: Spearhead the research and implementation of cutting-edge Transformer architectures and reinforcement learning models.
  • Roadmap Leadership: Own the technical roadmap for our 2026 release, ensuring feasibility and technical excellence across all engineering disciplines.
  • Optimization: Continuously refine model inference pipelines and reduce computational costs without sacrificing accuracy.
  • Collaboration: Partner with cross-functional teams including product managers, data scientists, and security experts to integrate AI seamlessly into our ecosystem.
  • Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD preferred.
  • Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years in a senior or lead role.
  • Technologies: Deep proficiency in Python, PyTorch, TensorFlow, and SQL.
  • Infrastructure: Strong experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
  • Algorithms: Solid understanding of MLOps, data pipelines, and distributed systems.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow AWS Kubernetes MLOps Machine Learning Deep Learning Distributed Systems

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