MLOps Engineer

*W2 Only*

Location: Pittsburgh, PA (5 days onsite)

Required skills/ experience:

1. Bachelor's degree in computer science, computer engineering, or relevant field.
2. Strong knowledge of data architecture in banking domain.
3. 4+ Years Work Experience in Python, Mongo.
4. Strong hands-on experience with Microsoft Azure.
5. Integrate LLMs with enterprise datasets using Azure Open AI.
6. Understanding of agentic frameworks (such as AutoGen or LangGraph, MCP).
7. ML: Familiar with CI/CD Pipeline, Jenkin, Model Training, Model Deployment.
8. GenAI: Knowledge in LLM Models, Langchain, Hugingface.

Job Responsibilities:

• Maintain existing predictive models while architecting for the future.
• Architecting application that works as an integration of predictive model and generative AI.
• Building and deploying predictive models based on Random Forest, Linear Regression, etc. for problems such as fraud detection, anomaly detection, churn prediction etc. at an enterprise scale.
• Develop robust and scalable pipelines for data preprocessing, model training, and deployment.
• Strong programming skills in Python and in similar languages.
• Familiarity with machine learning frameworks like PyTorch.
• Hands on experience with generative AI models such as GPT.
• Understanding of MLOps practices for building scalable AI pipelines.
• Solid understanding of natural language processing (NLP) and AI ethics.
• Translate complex requirements into scalable and efficient architecture
• Design and implement scalable ML pipelines with CI/CD automation, efficient model training, validation, and deployment across enterprise environments.
• Excellent Communication and Leadership qualities to work independently with minimal supervision.