About the Role
As an AI/ML Engineer at IQWorks, you will work on the core intelligence layer that powers our platform — the AIQ engine. You will design, train, and deploy models for PII detection, named entity recognition, data classification, and document understanding. A key focus of this role is building models that run on-premise and at the edge, enabling enterprises to process sensitive data without it ever leaving their infrastructure. Your work will directly impact how enterprises discover and protect sensitive data across structured and unstructured sources.
What You Will Do
- Develop and fine-tune NLP models for PII detection, named entity recognition, and text classification
- Build and maintain the data classification pipeline that powers DiscoverIQ and ClassifyIQ
- Design and implement model evaluation frameworks to measure precision, recall, and accuracy across data types
- Optimize models for on-premise and edge deployment — small footprint, low latency, and offline-capable inference
- Optimize model inference for cloud production workloads — latency, throughput, and cost efficiency
- Collaborate with product and engineering teams to integrate AI capabilities into the platform
- Research and prototype new approaches for document understanding, contextual classification, and anomaly detection
- Build training data pipelines and labeling workflows to continuously improve model quality
What We Are Looking For
- 3+ years of experience in machine learning engineering or applied AI
- Strong proficiency in Python and ML frameworks (PyTorch, Hugging Face Transformers, or similar)
- Hands-on experience with NLP tasks: NER, text classification, sequence labeling, or document understanding
- Experience deploying models to production — both cloud (FastAPI, Docker) and on-premise/edge environments
- Solid understanding of ML fundamentals: training, evaluation, overfitting, data quality, and model lifecycle
- Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns
- Strong problem-solving skills and ability to work independently in a fast-moving team
Nice to Have
- Experience with data privacy, PII detection, or compliance-related ML applications
- Experience with model quantization, distillation, or ONNX for edge deployment
- Background in building OCR or document processing pipelines
- Familiarity with LLM fine-tuning, prompt engineering, or agentic AI workflows
- Experience with Go or TypeScript for backend services
- Prior work at an early-stage startup shipping ML products end-to-end