AI/ML Engineer

Location: WOODLAND HILLS, CASkill Area Required Experience]Overall AI/ML Engineering Experience - 5+ Years Machine Learning Algorithms (Classification & Regression) - 4+ Years AutoML Tools (Sage Maker Autopilot / H2O / Auto Keras)2-3+ Years Python Programming - 4+ YearsML Libraries (Scikit-learn, Pandas, Num Py)3-4+ Years Model Fine-Tuning & Hyperparameter Optimization 2-3+ YearsAWS Sage Maker (Training, Deployment, Endpoints)2-3+ Years (Hands-on)Data Preprocessing & Feature Engineering 3+ Years Model Evaluation Techniques 3+ Years Version Control (Git)2+ YearsML Lifecycle / Model Management 2+ Years Skill Area Expected Exposure Tensor Flow / PyTorch 1-2+ YearsMLOps Tools & Practices 1-2+ YearsAWS Ecosystem (beyond Sage Maker) Working KnowledgeCI/CD for ML Workflows Basic-Intermediate Deep Learning Models Job Title: AI/ML Engineer Experience: 5+ Years Employment Type: Contract Job Summary We are seeking a skilled AI/ML Engineer with strong experience in building and deploying machine learning models, including classification and regression models, leveraging AutoML techniques, and performing model fine-tuning. The ideal candidate will have hands-on expertise in Python-based ML libraries and experience working with AWS Sage Maker for scalable model development and deployment.

Key Responsibilities: Design, develop, and deploy machine learning models for business use cases Work on classification and regression problems with structured and unstructured data Utilize AutoML frameworks to accelerate model building and optimization Perform model fine-tuning, hyperparameter optimization, and performance enhancement Develop and implement data pipelines for model training and evaluation Collaborate with cross-functional teams to translate business problems into ML solutions Deploy and manage ML models using AWS Sage Maker Monitor model performance and ensure continuous improvement Ensure best practices in data handling, model versioning, and reproducibility Required Skills & Qualifications Strong experience in Machine Learning algorithms (Classification & Regression) Hands-on experience with AutoML tools (e.g., Sage Maker Autopilot, H2O, Auto Keras, etc.) Proficiency in Python and major ML libraries: Scikit-learn Pandas, Num Py Tensor Flow / PyTorch (preferred) Experience in model fine-tuning and hyperparameter optimization Strong knowledge of AWS Sage Maker (training, deployment, endpoints) Good understanding of data preprocessing, feature engineering, and model evaluation Experience with version control (Git) and ML lifecycle management Preferred Skills Experience with MLOps practices and tools Knowledge of cloud services (AWS ecosystem) beyond Sage Maker Exposure to deep learning models and frameworks Familiarity with CI/CD pipelines for ML workflows Domain experience in healthcare, finance, or retail (optional)