Job Description
Shape the Future of Intelligence. Join Vertex AI Labs as we architect the AI systems that will define the year 2026 and beyond. We are not just building models; we are building the cognitive infrastructure for the next generation of enterprise solutions.
In this high-impact role, you will lead the development of Autonomous Agentic AI and Large Language Model (LLM) ecosystems. You will bridge the gap between theoretical research and scalable production deployment, ensuring our solutions are not only cutting-edge but also responsible, efficient, and safe.
Why You'll Love It Here
- Visionary Impact: Work on projects that are currently in the 'research phase' and will be industry standards by 2026.
- Unlimited PTO: We trust our experts to manage their own time.
- Top-Tier Stack: Access to the latest GPUs, H100 clusters, and open-source frameworks.
- Equity Package: Significant ownership in a rapidly scaling unicorn.
What You'll Do
- Architect and deploy next-generation Autonomous Agents capable of complex reasoning and multi-step decision making.
- Design and optimize RAG (Retrieval-Augmented Generation) pipelines to ensure factual accuracy and reduce hallucinations.
- Implement cutting-edge Model Quantization and Fine-tuning strategies to reduce inference costs by 40%+.
- Collaborate with product and engineering teams to integrate AI capabilities into seamless user experiences.
- Establish robust MLOps pipelines for continuous training, monitoring, and model governance.
What You Bring
- 5+ years of professional experience in Machine Learning Engineering or AI Research.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Proven track record of deploying LLMs to production environments (e.g., Hugging Face, LangChain, vLLM).
- Strong understanding of distributed systems, high-scale data processing (Spark, Kafka, Flink), and cloud infrastructure (AWS, GCP, or Azure).
- Familiarity with ethical AI practices, bias mitigation, and data privacy regulations (GDPR, CCPA).
- Ph.D. or Masters in Computer Science, Mathematics, or a related field is a strong plus.
Responsibilities
- Lead the design and implementation of Autonomous Agentic AI systems.
- Develop and optimize RAG pipelines for enterprise applications.
- Reduce inference costs through model quantization and fine-tuning.
- Build scalable MLOps infrastructure for continuous delivery.
- Ensure data quality and model performance monitoring.
Qualifications
- 5+ years in Machine Learning Engineering or AI Research.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Experience deploying LLMs in production (vLLM, Hugging Face).
- Strong background in Distributed Systems and Cloud Architecture.
- Knowledge of Ethical AI and bias mitigation.