PNC is looking for a Machine Learning Engineer with strong front-end development skills to bridge the gap between ML models and user interfaces, building intelligent, responsive, and scalable applications.
Requirements
- 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).
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.
- 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.
Other
- 3–6 years of experience in software engineering or ML engineering roles.
- 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.
- PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.
