Key skills
CloudGoogle Cloud PlatformPythonSQLAIMachine LearningMLGenAILLMLangChainMLOpsPineconeData EngineeringGCPGoogle Cloud
About this role
Role Overview
- Architect & Build: Design and implement end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud
- Engineer for Precision: Develop advanced RAG (Retrieval-Augmented Generation) pipelines and Semantic Search systems using GCP Vector Search or Pinecone
- Optimize Models: Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance
- Agentic Ops: Build and manage agentic workflows that automate complex multi-step reasoning tasks
- Collaborate & Innovate: Work directly with customers to understand requirements, suggest novel features, and implement state-of-the-art AI techniques
- Productionize: Apply MLOps best practices to ensure models are served efficiently, monitored, and continuously improved
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
- 5+ years of experience in AI/ML
- Proven track record of deploying GenAI products to a production environment
- Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus
- Knowledge of Data Engineering and SQL
Tech Stack
- Cloud
- Google Cloud Platform
- Python
- SQL
Benefits
- Comprehensive Health Insurance
- Paid Leave (Vacation/PTO)
- Paid Holidays
- Sick Leave
- Parental Leave
- Bereavement Leave
- 401 (k) Employer Match
- Employee Referral Bonuses