
Machine Learning Engineer - Data Science Innovation (DSI)
- Pittsburgh, PA
- Permanent
- Full-time
Machine Learning Engineering:
- Build, train, evaluate, and optimize machine learning models (e.g., classification, regression, NLP, recommendation).
- Implement pipelines for model deployment, monitoring, and retraining using MLOps best practices.
- Collaborate with data scientists to translate prototypes into production-ready code.
- Design scalable APIs and services to serve ML predictions to front-end components.
- Build and maintain modern, responsive, and accessible front-end interfaces using React (or equivalent framework).
- Integrate ML models and APIs into seamless user experiences.
- Optimize UI performance and ensure smooth, data-driven interactions.
- Translate business needs and wireframes into functional, elegant front-end features.
- 3–6 years of experience in software engineering or ML engineering roles.
- Proficiency in Python for ML development (e.g., scikit-learn, TensorFlow, PyTorch).
- Solid understanding of ML model lifecycles, versioning, and monitoring (e.g., MLflow, Weights & Biases).
- Proficient in front-end technologies: React.js, TypeScript/JavaScript, HTML5, CSS3.
- Experience with REST APIs or GraphQL and integrating with back-end services.
- Familiarity with CI/CD pipelines, Docker, and cloud platforms (AWS, GCP, or Azure).
- Experience deploying ML models using Flask, FastAPI, or similar frameworks.
- Experience with front-end design systems or component libraries (e.g., Angular UI, Tailwind CSS).
- Exposure to full-stack development or back-end technologies – Javascript.
- Knowledge of user-centric design and data privacy principles.
- Strong product mindset and ability to think end-to-end.
- Excellent collaboration skills — able to work across ML, engineering, and design.
- Agile and iterative development approach.
- Leverages analytical tools to provide business and technical expertise for the analytics process, tools and applications for a business function or business unit to create data driven solutions.
- Recommending appropriate performance measures to be produced including lifts, efficiencies, confidence intervals, and other statistical metrics.
- Analyzing and processing data, building and maintaining models and report templates, and developing dynamic, data-driven solutions.
- Providing business clients with detailed, actionable reports documenting the findings from, data processing, and data analysis.
- Consulting on using business intelligence data for predictive analytics and facilitating implementation of new tools and data marts.
- Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
- Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.