Technical Product Manager - Search, Summary, and Insight (On-site)

$135,500 - $213,400/Yr

Merck KGaA Darmstadt Germany

Full-time - Mid Level

Onsite

1,001-5,000 employees

Chemical Manufacturing

About the position

The Search, Summarize, and Insights Technical Product Manager will lead the development of Natural Language Processing (NLP) and Generative AI workflows aimed at enhancing knowledge management and generating insights from unstructured data. This role focuses on delivering tailored solutions for text understanding, particularly in drug discovery and development, while collaborating with cross-disciplinary teams to ensure the adoption of strategic visions in AI innovation and software product reuse.

Responsibilities

• Drive the development of NLP and Generative AI workflows for knowledge management.
• Lead the delivery of end-to-end solutions for text understanding use cases.
• Collaborate with technical leads and cross-functional teams to ensure strategic vision adoption.
• Engage with stakeholders to understand real-world challenges and develop automated data solutions.
• Implement and standardize ML and LLM operations for model evaluation and monitoring.
• Present approaches and impacts of team implementations to internal and external audiences.

Requirements

• Experience in product management, particularly with data- and ML-driven products from conception to deployment.
• Proven ability to lead agile software development teams and apply agile best practices.
• Familiarity with technical software development best practices, including continuous integration.
• Experience with Software Development Life Cycle (SDLC) management and compliance with documentation standards.
• Strong communication and teamwork skills, with a focus on scientific communication and mentorship.
• Proficiency in programming with Python and full-stack software development.
• Experience with version control and collaboration tools like git, and environment management tools.
• Knowledge of data engineering frameworks such as Apache Spark and orchestration frameworks like Airflow.
• Understanding of statistical learning methods, particularly in NLP contexts.
• Familiarity with NLP and Generative AI libraries and tools.

Nice-to-haves

• Experience with semantic search and retrieval frameworks.
• Knowledge of embedding models and retrieval approaches in the context of Retrieval Augmented Generation (RAG).
• Experience with ML/LLM Ops tooling such as MLFlow and LangFuse.

Benefits

• Bonus eligibility
• Long-term incentive opportunities
• Health care and insurance benefits for employees and families
• Retirement benefits
• Paid holidays
• Vacation and sick days