Senior NLP Data Engineer

About the Role

Key Responsibilities

• Design, build, and operate data tools, services, workflows, and pipelines that deliver high value through AI-driven products using modern data engineering tools (e.g., Spark, Kafka, Storm) and orchestration tools (e.g., Google Workflow, AirFlow Composer).
• Partner with AIML and knowledge graph platform teams to build, test, and deploy NLP and GenAI pipelines, systems, and solutions.
• Apply graph-based data modeling techniques for efficient organization, integration, and data retrieval to ensure system flexibility and maintainability.
• Produce well-engineered software, including automated test suites, technical documentation, and operational strategies.
• Identify opportunities to reuse modular code and develop microservices to improve efficiencies.
• Contribute to the roadmaps of upstream teams (e.g., Data Platforms, DataOps, DevOps) to enhance overall program effectiveness.
• Ensure consistent application of platform abstractions for logging and lineage to maintain quality and traceability.
• Participate in code reviews, adhere to coding best practices, and promote team standards.
• Follow QMS framework and CI/CD best practices, and help improve them for better ways of working.
• Provide leadership and mentorship to team members to ensure high-quality delivery and operational robustness.

Requirements

• Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related discipline.
• 5+ years of industry experience in data engineering.
• Knowledge of NLP and GenAI techniques, experience processing unstructured data, using vector stores, and approximate retrieval.
• Experience building end-to-end systems based on machine learning or deep learning methods.
• Experience overcoming high volume, high compute challenges.
• Familiarity with orchestrating tooling.
• Cloud experience (e.g., AWS, Google Cloud, Azure).
• Experience with automated testing and design.
• Experience with DevOps practices.
• Deep knowledge of at least one programming language (e.g., Python, Scala, Java).
• Experience with big data tools (e.g., Spark, Kafka, Storm).
• Proven experience with machine learning algorithms and NLP frameworks like Pytorch, TensorFlow, Spacy.
• Experience with CI/CD implementations using git and tools like Jenkins, CircleCI, GitLab, Azure DevOps.
• Experience working in agile environments using tools like Jira and Confluence.
• Experience with Infrastructure as Code and automation tools such as Terraform.

Nice to Have

• Master's or PhD in Data Engineering, Computer Science, Software Engineering, or related discipline.
• Good understanding of ontologies and semantic harmonization of data across sources.
• Experience implementing Generative AI solutions.
• Proven track record working with knowledge graphs and graph databases.
• Proficiency in semantic web technologies (SPARQL, RDF, OWL).
• Experience working with complex biomedical datasets, including genomics, proteomics, and high-throughput screening.

Benefits & Perks

• Visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.