AIML Engineer

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Who we are

CAI is a global services firm with over 9000 associates worldwide and a yearly revenue of $1.3 billion. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients colleagues and communities. As a privately held company we have the freedom and focus to do what is rightwhatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

Job Description

We are looking for an AI/ML Engineer to design and implement scalable AI/ML solutions for engineering challenges. This position will be full-time and remote.

What Youll Do

• Develop and maintain high-performance AI/ML infrastructure (local and cloud-based) to support AI hub projects and engineering users

• Build and deploy scalable machine learning pipelines using TensorFlow PyTorch Keras and other deep learning frameworks for production environments

• Implement classical machine learning algorithms including regression models classification algorithms clustering techniques dimensionality reduction methods and ensemble methods (Random Forests XGBoost LightGBM)

• Design and deploy deep learning architectures including Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs) Long Short-Term Memory networks (LSTMs) autoencoders and transformer architectures for non-generative tasks

• Apply inverse design principles to optimize engineering solutions using AI-driven approaches enabling data-driven design optimization

• Develop physics-informed neural networks (PINNs) and hybrid AI models that integrate engineering domain knowledge with machine learning capabilities

• Implement surrogate modeling techniques to accelerate engineering simulations and enable real-time optimization

What Youll Need

Required:

• 4-6 years of relevant experience

• Proven track record of developing and deploying AI/ML solutions for engineering scientific or industrial applications

• Demonstrated experience in successfully delivering end-to-end machine learning projects from conception to production deployment

• Deep understanding of classical machine learning algorithms: linear regression logistic regression Support Vector Machines (SVM) decision trees random forests gradient boosting machines (XGBoost LightGBM CatBoost) k-means clustering hierarchical clustering Principal Component Analysis (PCA) and other dimensionality reduction techniques

• Strong expertise in deep learning architectures: Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs) Long Short-Term Memory networks (LSTMs) Gated Recurrent Units (GRUs) autoencoders variational autoencoders attention mechanisms residual networks (ResNets) and transformer architectures for non-generative applications

• Hands-on experience with TensorFlow PyTorch Keras scikit-learn XGBoost and related ML/DL libraries and frameworks

• Knowledge of inverse design principles optimization algorithms (gradient descent variants genetic algorithms particle swarm optimization) and AI-driven engineering design methodologies

• Experience with physics-informed machine learning multi-objective optimization and constraint-based optimization

• Familiarity with computer vision techniques time-series analysis anomaly detection and predictive maintenance applications

• Understanding of feature engineering feature selection data augmentation techniques and handling imbalanced datasets

• Experience with model interpretability and explainable AI techniques (SHAP LIME attention visualization feature importance analysis)

• Knowledge of transfer learning domain adaptation and few-shot learning techniques

• Understanding of neural network optimization loss function design and training strategies for complex engineering problems

Physical Demands

• Ability to safely and successfully perform the essential job functions

• Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings etc.

• Ability to conduct repetitive tasks on a computer utilizing a mouse keyboard and monitor

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application interviewing completing any pre-employment testing or otherwise participating in the employment selection process please direct your inquiries to or (888).