
Machine Learning Engineer
19 hours ago
About the Role
We are seeking a skilled professional to design and implement intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure.
This role involves creating machine learning pipelines for automating loan origination, underwriting, and document intelligence processes.
Key Responsibilities
- Design ML/NLP/GenAI pipelines for process automation.
- Develop LLM-based solutions using Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks.
- Build Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents.
- Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering.
- Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models.
- Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services).
- Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions.
- Leverage prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores for contextual mortgage document workflows.
Required Skills & Qualifications
- 5+ years of experience in machine learning, NLP, or LLM-based systems.
- Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design.
- Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers.
- Strong knowledge of Azure Cloud – including Azure ML, Azure Functions, Azure DevOps.
- Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow.
- Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate).
- Experience deploying models into production-scale environments.
- Nice to Have
- Understanding of US mortgage or lending workflows (1003, 1008, bank statements, etc.).
- Experience with OCR, document intelligence tools (Azure Form Recognizer, Amazon Textract).
- Exposure to Agentic AI concepts such as autonomous agents, planning, memory chaining.
- Knowledge of privacy and compliance frameworks (HIPAA, SOC2) in AI deployments.
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