Description & Requirements
We are seeking an Associate AI Engineer to join the Maximus IR&D Team. In this role, you will build and optimize production pipelines to extract insights from unstructured text and scanned document images. This position involves a dynamic mix of Python for machine learning prototyping and Rust for building high-performance data processing services.
As an associate-level role within our research group, we value strong foundational software skills, a proven machine learning project portfolio, and an eagerness to learn new systems programming languages like Rust on the job.
Essential Duties and Responsibilities:
- Design and build customer experience and conversational AI solutions, including dialog flows, API integrations and AI agent orchestrations.
- Develop and maintain technical integrations between solutions and Maximus technologies such as CRM, ITSM, and data reporting systems.
- Create comprehensive technical documentation, deployment guides, infrastructure-as-code templates and conduct internal training sessions on implemented solutions.
- Collaborate with internal and external stakeholders to gather requirements, present solution designs, and provide ongoing technical support.
- Research emerging customer experience and conversational AI technologies, evaluate new tools and platforms, upskill on emerging customer experience innovations, and contribute to continued improvement of Maximus solutions offerings.
- Document AI Pipelines: Design systems to process, cleanse, and classify unstructured text and layout-heavy scanned documents.
- Model Development: Train, tune, and optimize machine learning, deep learning, and neural network models for classification and prediction tasks.
- Hybrid Systems Engineering: Write clean, modular Python code for ML modeling and collaborate on migrating performance-critical pipeline services to Rust.
- Feature Engineering: Apply statistical feature engineering and advanced data preprocessing to complex, unstructured data formats.
- Bachelors Degree or equivalent experience and 0+Years
- Education: Bachelor’s or advanced degree in Computer Science.
- Mathematics: Strong academic foundation in linear algebra, calculus, and probability/statistics.
- Programming & Libraries: High proficiency in Python (including SciKit-learn and PyTorch).
- Machine Learning Foundations: Practical experience building, evaluating, and tuning supervised and unsupervised models (e.g., classification, clustering, neural networks, or embeddings).
- Tools & Infrastructure: Experience with version control (Git/GitHub), containerization (Docker), and cloud environments (AWS or cloud alternatives).
Preferred experience
- Experience or strong interest in systems programming with Rust.
- Familiarity with building synthetic data frameworks or simulating dataset risk metrics.
- Understanding of model interpretability frameworks or feature importance analysis.