Senior Machine Learning Engineer

About the Role

Join our AI & Analytics practice to design and deploy production machine learning systems for government and commercial clients. You will build end-to-end ML pipelines - from data engineering and model development to deployment and monitoring - solving complex problems at enterprise scale.

Responsibilities

• Design and implement production machine learning models for client engagements across government and enterprise
• Build scalable ML pipelines using cloud-native services (SageMaker, Vertex AI, Azure ML)
• Collaborate with data engineers to architect robust data ingestion and feature engineering pipelines
• Deploy models with proper monitoring, drift detection, and automated retraining capabilities
• Present findings and recommendations to senior client stakeholders and executives
• Mentor junior data scientists and contribute to AI practice growth and IP development

Qualifications

• Master’s or PhD in Computer Science, Statistics, or related quantitative field
• 5+ years of experience building and deploying production ML models
• Proficiency in Python, SQL, and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, or Azure ML)
• Strong understanding of MLOps practices including CI/CD for ML, model monitoring, and experiment tracking
• US citizenship or ability to obtain a security clearance preferred