Machine Learning Engineer

We are partnering with a leading financial services client in Phoenix to hire a Data Science / Machine Learning Engineer to support the development and deployment of advanced analytics and AI-driven solutions. This role is ideal for someone who thrives in a fast-paced environment and has hands‑on experience building, optimizing, and deploying machine learning models at scale. Location: Phoenix, AZ (Hybrid – 3 days onsite per week) Duration: Contract – Potential for Extension/Conversion Key Responsibilities Design, develop, and deploy machine learning models for real-world financial use cases Work across the full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring Build and implement both classical machine learning models (e.g., regression, classification, clustering) and NLP solutions (e.g., text classification, entity recognition, sentiment analysis) Collaborate with data engineers and business stakeholders to translate business requirements into scalable ML solutions Optimize model performance and ensure reliability in production environments Develop APIs and integrate ML models into existing enterprise systems Maintain proper documentation and ensure model governance, compliance, Required Qualifications 5+ years of experience in Data Science, Machine Learning Engineering, or a related field Proven hands‑on experience building and deploying ML models in production environments Strong experience with Python and ML libraries such as scikit-learn, TensorFlow, PyTorch Experience with Natural Language Processing (NLP) techniques and frameworks (e.g., NLTK, spaCy, transformers) Experience with data manipulation and analysis using Pandas, NumPy Familiarity with cloud platforms such as AWS, Azure, or GCP Strong understanding of model evaluation, tuning, and performance optimization #J-18808-Ljbffr