Machine Learning Engineer (MLOps)

Job Role: Machine Learning Engineer (MLOps)

Location: Austin, Texas (Onsite)

Type: 1099 Contract | C2H

Job Description:

• Experienced Machine Learning Engineer with 8-10+ years of hands-on expertise deploying and scaling machine learning models in production environments. 
• Skilled in operationalizing complex models and integrating them into enterprise systems with a focus on performance, scalability, and governance.
• Partner with data science and engineering teams to deliver, optimize, and maintain production-grade ML models and pipelines.
• Deploy and manage end-to-end machine learning workflows, from model development to operational monitoring.
• Proficient in core ML algorithms such as Regression, Classification, and Natural Language Processing (sentiment analysis, topic modeling, TF-IDF).
• Experienced with tools and frameworks including Scikit-learn, VADER Sentiment, Pandas, and PySpark.
• Design and maintain dynamic data pipelines tailored to specific use cases.
• Integrate machine learning solutions within business workflows, ensuring seamless coordination across upstream and downstream systems.
• Develop and automate reporting pipelines for model performance metrics to support Model Risk Oversight and governance reviews.
• Create and maintain runbooks for ongoing model support, versioning, and operational maintenance.