Job Description
Are you ready to architect the future? Apex Neural Systems is seeking a visionary Lead AI Architect to spearhead our 2026 Strategic Horizon Initiative. We are building the next generation of adaptive intelligence systems, and we need a technical mastermind to define the roadmap.
In this pivotal role, you will not just write code; you will shape the ethical frameworks and architectural blueprints that will power enterprise solutions for the next decade. Join a team of elite engineers and researchers dedicated to pushing the boundaries of Machine Learning and Deep Learning.
Why Join Us?
- Work on cutting-edge Generative AI and Autonomous Agent technologies.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with quarterly in-person innovation sprints in Austin.
Responsibilities
- Strategic Roadmapping: Define the technical architecture and milestones for the 2026 product roadmap, focusing on scalable AI infrastructures.
- Model Development: Lead the design and implementation of large-scale deep learning models, ensuring high accuracy and low latency.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- System Optimization: Oversee the optimization of neural networks and data pipelines to handle petabyte-scale datasets efficiently.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for non-technical stakeholders and investors.
- Ethical AI Governance: Establish and enforce guidelines for bias mitigation and responsible AI deployment.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering and machine learning, with at least 3 years in a leadership or architectural role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Apache Spark, Kubernetes).
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Proficiency: Strong experience deploying models on AWS, Azure, or GCP.
- Problem Solving: Proven ability to solve complex, ambiguous problems with innovative technical solutions.