Senior MLOps Engineer
Indexed description
*W2 Only* *Student visa applicants won't be considered*
Location: Pittsburgh, PA (5 days onsite)
Required skills/ experience:
- Bachelor's degree in computer science, computer engineering, or relevant field.
- Strong knowledge of data architecture in banking domain.
- 4+ Years Work Experience in Python, Mongo.
- Strong hands-on experience with Microsoft Azure.
- Integrate LLMs with enterprise datasets using Azure Open AI.
- Understanding of agentic frameworks (such as AutoGen or LangGraph, MCP).
- ML: Familiar with CI/CD Pipeline, Jenkin, Model Training, Model Deployment.
- 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.
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