Job Description
Are you ready to architect the technology of tomorrow? Apex Future Systems is seeking a visionary Senior AI Engineer to join our elite team in San Francisco.
In this pivotal role, you will define the technological landscape for 2026 and beyond, building autonomous systems that redefine human-machine interaction. We are not just predicting the future; we are building it.
As a key member of our Project 2026 initiative, you will work on cutting-edge Generative AI, Large Language Models (LLMs), and autonomous agents designed to revolutionize enterprise efficiency.
We offer a competitive salary, substantial equity packages, and the autonomy to push the boundaries of what is possible in AI.
Responsibilities
- Architect Intelligent Systems: Design and deploy scalable AI infrastructure capable of handling complex, high-volume data streams for next-generation applications.
- Model Optimization: Fine-tune and optimize Large Language Models (LLMs) to achieve peak performance, accuracy, and low latency in production environments.
- R&D Leadership: Spearhead research initiatives exploring emerging paradigms in Generative AI, reinforcement learning, and multimodal systems.
- System Integration: Bridge the gap between theoretical AI models and real-world production environments, ensuring seamless integration with existing tech stacks.
- Ethical AI & Governance: Implement robust guardrails and safety protocols to ensure AI outputs are fair, transparent, and aligned with ethical standards.
- Talent Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence, continuous learning, and innovation.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a proven track record of shipping production-grade AI models.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Kubeflow, MLflow, Docker, Kubernetes).
- Language Model Expertise: Deep understanding of transformer architectures, attention mechanisms, and experience with LLM fine-tuning and prompt engineering.
- Problem Solving: Ability to tackle complex, ambiguous problems with creative, robust, and scalable engineering solutions.
- Communication: Exceptional ability to translate complex technical concepts into actionable insights for non-technical stakeholders.