Machine Learning / AI Engineer in a consulting firm, developing AI models and enhancing GovHorizon platform. Collaborating with teams to operationalize AI and ensure model performance.
Responsibilities
Build, train, and optimize Machine Learning and AI models for strategic use cases such as regulatory forecasting, text analysis, and predictive intelligence
Prepare, clean, and validate data, performing feature engineering to ensure high-quality model inputs
Collaborate with engineering teams to deploy models into production using APIs and MLOps pipelines
Monitor model performance and implement automated retraining, drift detection, and performance metrics
Document model workflows, architectures, and experimental results
Contribute to the definition and implementation of MLOps practices and model lifecycle management tools
Requirements
3–5 years of experience in Machine Learning, Data Science, or AI Engineering roles
Strong proficiency in Python and Machine Learning libraries such as scikit-learn, TensorFlow, PyTorch, or equivalent
Knowledge of data pipelines, ETL/ELT processes, and orchestration frameworks such as Airflow or Kubeflow
Experience with cloud-based ML services and deployment platforms, such as Azure Machine Learning, Databricks, AWS SageMaker, or GCP Vertex AI
Solid understanding of model performance metrics, validation techniques, and result evaluation
Benefits
Health and life insurance
25 days of annual leave
Support for professional development, training, and certifications
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