H1 - AI Scientist
Requirements
• 5+ years of hands-on experience in machine learning, data science, or applied AI roles • Strong proficiency in Python; working knowledge of SQL and R • Deep experience with ML frameworks such as TensorFlow and PyTorch • Proven experience building and running models on large-scale data pipelines using Apache Spark (PySpark) • Exposure to NLP techniques — including text classification, named entity recognition, information extraction, and transformer-based models • Familiarity with cloud platforms (Azure preferred) and tools such as Databricks, Delta Lake, and Kubernetes • Experience working closely with data engineering and MLOps teams in production environments • Background in healthcare, life sciences, pharma, or clinical research is highly preferred • Comfortable working independently in a remote setting with a distributed, cross-timezone team • Generous paid time off & pre-planned company-wide wellness holidays • Retirement options • Health & charitable donation stipends • Impactful Business Resource Groups
Responsibilities
• Design, develop, and deploy machine learning models to extract insights from clinical and healthcare data — including NLP tasks across publications, trial records, and medical claims • Build and optimize ML pipelines on large-scale distributed systems using Apache Spark and cloud-native tools • Work with structured and unstructured data sources to develop predictive models, classification systems, and entity resolution approaches • Collaborate with data engineers to integrate ML models into production ETL pipelines and ensure scalability and reliability • Partner with MLOps teams to operationalize models — including monitoring, retraining, and versioning workflows • Evaluate and benchmark model performance and present findings to both technical and non-technical stakeholders • Stay current with advances in NLP, deep learning, and healthcare-specific AI applications to identify opportunities for innovation
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