
AI/ML Model Development Specialist
1 day ago
Advanced AI/ML Model Developer
">We are seeking a seasoned professional to design and deploy sophisticated AI/ML models for mortgage automation agents. This role involves crafting predictive models for creditworthiness, fraud detection, income verification, document analysis, and conversational interfaces.
">Required Expertise">- ">
- Extensive experience with Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face Transformers.">
- Specialized knowledge in NLP: Named Entity Recognition (NER), text summarization, question answering, and OCR techniques using Tesseract, Amazon Textract, and Azure Form Recognizer.">
- A deep understanding of statistical modeling, risk scoring, credit analytics, and fraud detection methodologies.">
- Familiarity with vector databases such as Pinecone, Weaviate, FAISS, and Milvus.">
- Experience with MLOps tools like MLflow, Kubeflow, and Weights & Biases.">
- Strong foundation in responsible AI practices, including fairness, accountability, and transparency.">
This role offers an exciting opportunity to work at the forefront of AI/ML innovation, developing solutions that drive business growth and customer satisfaction.
">About the Opportunity
">We are looking for a talented individual who can leverage their expertise to create cutting-edge models that power our mortgage automation agents.
">What You'll Do
">- ">
- Craft advanced AI/ML models for creditworthiness prediction, fraud detection, and income verification.">
- Analyze documents using OCR techniques and natural language processing.">
- Develop conversational interfaces that provide seamless customer experiences.">
- Collaborate with cross-functional teams to integrate models into our mortgage automation agents.">
This is an excellent chance to join our team and contribute to the development of innovative AI/ML solutions that transform the mortgage industry.
">Key Responsibilities
">- ">
- Design and develop predictive models using Python, PyTorch, TensorFlow, and Scikit-learn.">
- Implement NLP techniques for text analysis, named entity recognition, and question answering.">
- Optimize model performance using vector databases and MLOps tools.">
- Ensure model explainability, fairness, and compliance with regulatory frameworks.">
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