Senior AI/ML Engineer

Job description

Beghou brings over three decades of experience helping life sciences companies optimize their commercialization through strategic insight, advanced analytics, and technology. From developing go-to-market strategies and building foundational data analytics infrastructures to leveraging artificial intelligence to improve customer insights and engagement, Beghou helps life sciences companies maximize performance across their portfolios. Beghou also deploys proprietary and third-party technology solutions to help companies forecast performance, design territories, manage customer data, organize, and report on medical and commercial data, and more. Headquartered in Evanston, Illinois, we have 10 global offices. *Our mission is to bring together analytical minds and innovative technology to help life sciences companies navigate the complexity of health care and improve patient outcomes.* You will play a key role in designing, developing, and deploying AI solutions tailored to pharmaceutical clients. You will collaborate with cross-functional teams including data scientists, business consultants, and software developers to translate complex life sciences challenges into AI-driven innovations ### We'll trust you to: - Design and implement AI/ML pipelines that solve real-world problems in life sciences (e.g., territory alignment, rep scheduling, patient segmentation, incentive compensation optimization). - Work closely with domain consultants to understand client requirements and develop tailored AI solutions. - Lead efforts in data ingestion, feature engineering, and model development across structured and unstructured data sources (e.g., sales data, KOL feedback, medical claims). - Build and deploy scalable AI services and LLM-based copilots (e.g., for field force, MSLs, or commercial analytics teams). - Implement GenAI and Agentic AI frameworks for commercial automation. - Conduct technical reviews and provide mentoring to junior AI team members. - Collaborate with DevOps and cloud teams to deploy models on AWS/Azure. - Present technical concepts and outcomes to internal stakeholders and client teams. ### You'll need to have: - At least 7 years of experience in AI/ML engineering. - Proficient in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow, LangChain, Hugging Face). - Experience building and deploying machine learning models in production. - Strong understanding of MLOps tools and practices (e.g., MLflow, Docker, Git, CI/CD). - Exposure to LLMs, transformers, and retrieval-augmented generation (RAG) techniques. - Experience working with cloud environments (AWS, Azure preferred, Databricks). - Excellent communication skills with the ability to explain complex technical ideas to non-technical stakeholders. - Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.