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
• Experience developing APIs (e.g., Flask, FastAPI) for model deployment
• Strong understanding of model evaluation, tuning, and performance optimization