AI/ML Engineer
Intelligence That Ships, Not Just Experiments
Machine learning pipelines, LLM integration, data engineering.
Why Choose Us for AI/ML Engineer
Production AI systems, not notebook demos
LLM integration with safety guardrails
RAG pipeline architecture
MLOps and model monitoring
Real AI products shipped across our ventures
What You Get
A HavenWizards AI/ML Engineer builds intelligence that ships to production — not Jupyter notebooks that sit in research. They design LLM integration patterns, build AI-powered features with proper guardrails, and deploy machine learning pipelines that run reliably at scale. Every AI feature ships with content governance (prompt validation, output sanitization, cost tracking) and is monitored for quality degradation. They understand that AI in production means handling failures gracefully, not just getting the happy path working.
Systems We Build
- LLM integration — prompt engineering, model selection, response parsing, streaming
- AI feature development — chat interfaces, content generation, classification, summarization
- Content guardrails — prompt injection prevention, output validation, forbidden term blocking
- RAG pipelines — document ingestion, chunking, embedding, vector search, retrieval optimization
- ML pipeline automation — training workflows, model versioning, A/B testing, rollback
- Cost optimization — token tracking, model routing, caching strategies, batch processing
- Data engineering — ETL pipelines, data cleaning, feature engineering, dataset management
- Computer vision — image classification, OCR, object detection, visual search
- Monitoring & observability — quality metrics, drift detection, latency tracking, error rates
- AI safety & compliance — PII handling, bias detection, audit trails, usage policies
Skills & Tools
Ready to Deploy a AI/ML Engineer?
Every role ships with our DIOSH governance framework — structured onboarding, quality gates, and delivery accountability from day one.