About the Role
As an AI/ML Engineer at IQWorks, you will work on the AI that powers our platform. You will build, fine-tune, and deploy models for PII detection, named entity recognition, data classification, and document understanding. A key focus of this role is optimizing and deploying 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
- Build, fine-tune, and adapt NLP models for PII detection, named entity recognition, and text classification
- Build and maintain the data classification capabilities behind our data discovery and classification products
- 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 modern ML frameworks
- Hands-on experience with NLP tasks: NER, text classification, sequence labeling, or document understanding
- Experience deploying models to production in both cloud 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
- Effective use of AI as a force multiplier in your own workflow — accelerating research, experimentation, and delivery — with sharp judgment about where human oversight is essential so quality is never compromised
- 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 other optimization techniques 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 a high-growth startup shipping ML products end-to-end