Architect AI Engineer / AI Evangelist, Healthcare Business Unit (EMEA)

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or related field.
• 7+ years of experience in data science or machine learning roles, ideally with exposure to healthcare projects.
• Strong knowledge of ML frameworks such as scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
• Proficiency in Python for data science and related libraries (NumPy, pandas, matplotlib, seaborn, etc.).
• Experience working with large datasets and data processing frameworks (e.g., Spark, Dask, SQL).
• Understanding of MLOps concepts and tools (e.g., MLflow, Kubeflow, Vertex AI, Azure ML).
• Familiarity with cloud environments (Azure, AWS, or GCP) for training and deploying models.
• Experience with model interpretability, fairness, and explainability techniques.
• Strong communication and visualization skills for storytelling with data.
• English proficiency at Upper-Intermediate level or higher.

Preferred Qualifications (Nice to Have)

• Experience working with medical data (EHR, imaging, wearables, clinical trials, etc.).
• Familiarity with healthcare regulations related to data and AI (e.g., HIPAA, GDPR, FDA AI/ML guidelines).
• Knowledge of FHIR, HL7, or other healthcare interoperability standards.
• Practical experience with deep learning models (e.g., CNNs for imaging, transformers for NLP).
• Involvement in presales, proposal writing, or technical advisory work.

Job responsibilities

• Lead the design and development of AI/ML solutions across HealthTech and MedTech projects.
• Participate in technical presales by analyzing business cases and identifying opportunities for AI/ML application.
• Build and validate predictive models, classification systems, NLP workflows, and optimization algorithms.
• Collaborate with software engineers, cloud architects, and QA to integrate models into scalable production systems.
• Define and guide data acquisition, preprocessing, labeling, and augmentation strategies.
• Contribute to the development of GlobalLogic’s healthcare-focused AI accelerators and reusable components.
• Present technical solutions to clients, both business and technical audiences.
• Support model monitoring, drift detection, and retraining pipelines in deployed systems.
• Ensure adherence to privacy, security, and compliance standards for data and AI usage.
• Author clear documentation and contribute to knowledge sharing within the Architects Team.