Senior AI Engineer in Chicago

Senior AI Engineer

We are seeking a Senior AI Engineer with more than six years of experience designing, developing, and maintaining AI-based systems. The ideal candidate will have advanced expertise in Python, R, and Java
, with deep knowledge of machine learning algorithms, neural networks, data modeling, and secure AI practices
. This role involves architecting intelligent solutions, guiding AI strategy, and mentoring junior engineers, while ensuring scalability, security, and compliance in enterprise AI systems.

• Lead the design, development, and deployment of AI and machine learning systems
  .
• Architect secure AI models using encryption methods and compliance standards.
• Build and optimize neural network–based solutions to address business needs.
• Translate business requirements into scalable AI/ML models and intelligent applications.
• Oversee data modeling, engineering, and preprocessing pipelines
  .
• Integrate cloud‑based AI and machine learning services (AWS Sage Maker, Azure ML, GCP AI).
• Drive MLOps practices for continuous deployment, monitoring, and retraining of models.
• Communicate complex AI concepts effectively to both technical and business stakeholders.
• Mentor junior AI engineers and contribute to AI capability building across teams.
• Ensure compliance with secure AI development practices and emerging AI governance frameworks.

• Advanced expertise in Python, R, and Java for AI/ML development.
• Strong knowledge of machine learning models, algorithms, and encryption methods
  .
• Deep understanding of neural networks and their applications in AI solutions.
• Expertise in data modeling, engineering, and preprocessing
  .
• Proficiency in secure AI practices
  , including compliance and governance.
• Familiarity with cloud-based AI/ML services (AWS, Azure, GCP).
• Strong ability to communicate AI concepts to technical and non-technical audiences.

• Experience designing AI/ML architecture at the enterprise level.
• Hands‑on experience with MLOps pipelines (CI/CD for ML, monitoring, retraining).
• Knowledge of deep learning frameworks (Tensor Flow, PyTorch, Keras).
• Familiarity with ethical AI practices and emerging regulatory standards.
• Leadership experience mentoring AI teams or leading research initiatives.
• Exposure to big data ecosystems (Hadoop, Spark, Kafka) for large‑scale AI training.