Associate Engineer, AI Solutions

• 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.

JOB SPECIFIC DUTIES:

• 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.

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., ‘- 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.

$77,000

Maximum Salary

$85,000