Machine Learning Engineer

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company's success. As a Machine Learning Engineer within PNC's Data Science Innovation (DSI) organization, you will be based in Pittsburgh, PA. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis. Some responsibilities may be performed remotely, at manager's discretion.

We are looking for a versatile and product-oriented Machine Learning Engineer with strong front-end development skills to join our team. You will bridge the gap between cutting-edge ML models and intuitive user interfaces helping us build intelligent, responsive, and scalable applications. You will work closely with data scientists, backend engineers, and product teams to bring ML-powered features to life.

Key Responsibilities:

• 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.

Front-End Development:

• 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.

Required Qualifications:

• 36 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).

Preferred Qualifications:

• 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.

Soft Skills:

• 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.