Job Description
Are you ready to architect the future of intelligence? Vertex AI Labs is seeking a visionary Generative AI Engineer to lead our mission in building the AI systems of 2026. We are not just building today's tools; we are designing the autonomous agents and multi-modal systems that will define the next era of human-computer interaction.
In this role, you will bridge the gap between theoretical research and production-grade deployment, working with state-of-the-art Large Language Models (LLMs) and reinforcement learning agents. If you are passionate about ethical AI, scalability, and the cutting edge of technology, we want to hear from you.
Responsibilities
- Architect Production-Ready AI Pipelines: Design, train, and fine-tune proprietary Large Language Models and multi-modal systems for high-scale enterprise deployment.
- Optimize Inference & Efficiency: Implement model quantization, distillation, and caching strategies to ensure sub-100ms latency on edge devices and cloud infrastructure.
- Develop Agentic Workflows: Build autonomous AI agents capable of complex reasoning, planning, and tool use to automate enterprise workflows.
- Ensure Safety & Compliance: Implement guardrails, content moderation, and ethical alignment protocols to prevent hallucinations and ensure regulatory compliance (GDPR, CCPA).
- Research & Prototype: Experiment with emerging architectures (e.g., Mixture of Experts, State-Space Models) to push the boundaries of model capability.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on Machine Learning, AI, or Deep Learning.
- Experience: 5+ years of professional experience in software engineering and machine learning, with at least 2 years specifically focused on Generative AI and LLMs.
- Technical Stack: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of Hugging Face Transformers, LangChain, and LlamaIndex.
- Infrastructure: Strong experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
- Mathematical Foundation: Strong grasp of linear algebra, calculus, probability theory, and optimization techniques.