AI Engineer

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled AI Engineer to join our innovative team. AI Engineer | About You As an AI Engineer, you will design, develop, and demonstrate AI and machine learning solutions that address real-world business challenges across forecasting, risk scoring, churn prediction, anomaly detection, and optimization. You will work closely with sales engineering, data engineering, and business teams to rapidly translate client requirements into compelling PoCs and scalable AI/ML solutions. The ideal candidate combines strong machine learning expertise with Python development, cloud-based AI/ML platforms, MLOps fundamentals, and the ability to clearly present technical solutions to both technical and non-technical stakeholders. AI Engineer | Day-to-Day • Design and develop AI/ML PoCs, prototypes, and demonstrations using structured and tabular data for forecasting, risk scoring, churn prediction, optimization, and related business use cases. • Build, train, tune, and evaluate machine learning models using supervised, unsupervised, and semi-supervised techniques, including XGBoost, CatBoost, LightGBM, clustering, PCA, anomaly detection, and time-series modeling. • Develop AI/ML workflows using cloud platforms such as AWS SageMaker, Azure Machine Learning, or Databricks ML, supporting scalable model experimentation, training, and deployment. • Collaborate with data engineering teams to design data ingestion, preprocessing, feature engineering, and transformation pipelines using Python, Spark, and cloud-native technologies. • Partner with sales engineering and business stakeholders during pre-sales discussions, demonstrations, and technical workshops, translating business challenges into practical AI/ML solutions and effectively communicating model insights and business value. • Apply MLOps and AI engineering best practices across model evaluation, explainability, versioning, deployment, performance monitoring, drift detection, and optimization while developing reusable AI assets for transition to delivery teams. AI Engineer | Skills & Experience • 1+ years of hands-on AI/ML experience, developing and deploying machine learning models in production, prototype, or PoC environments, particularly using structured or tabular datasets. • Strong proficiency in Python and machine learning libraries, including Pandas, Scikit-learn, XGBoost, CatBoost, LightGBM, NumPy, or similar technologies. • Strong understanding of applied machine learning techniques, including feature engineering, model tuning, cross-validation, error analysis, clustering, anomaly detection, dimensionality reduction, and time-series modeling. • Hands-on experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure Machine Learning, Databricks ML, or comparable technologies. • Working knowledge of MLOps practices, including model versioning, deployment automation, model explainability, performance monitoring, and model/data drift detection. • Strong communication and presentation skills, with the ability to present AI/ML PoCs, technical approaches, model results, and business value to both technical and non-technical stakeholders.