AIML Services- Data Platform Engineer

GSK

4d

About The Position

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics, and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI. We're looking for a highly skilled individual contributor who can consistently take a poorly defined business or technical problem, work it to a well-defined problem/specification, and execute on it at a high level. They have a strong focus on metrics, both in the domains of system health/performance and the impact of their work. They are a model for the team on best practices for software development in general (and their specialization in particular), including code quality, documentation, DevOps practices, and testing, and coaching/mentorship. They ensure the robustness of our services and serve as an escalation point in the operation of existing services, pipelines, and workflows. This individual should be deeply familiar with the tools of their specialization and of their customers and engaged with the open-source community surrounding them – potentially, even to the level of contributing pull requests. The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.

Requirements

• Bachelor's or graduate degree in Computer Science, focused on software or data engineering, high-performance computing, or machine learning or 5+ years of industry experience in software/data/machine learning engineering.
• 2+ years of industry experience in software engineering.
• Experience in Python.
• Experience in applying CI/CD implementations using git and a common CI/CD stack (e.g. Jenkins, CircleCI, GitLab, Azure DevOps)
• Experience in API design principles, protocols, and tools (REST, GraphQL, Swagger, etc.)
• Experience in data system/ETL design principles, protocols, and tools (REST, GraphQL, Swagger, etc.)
• Experience developing infrastructure using Cloud services in GCP or similar cloud environment.
• Experience working with Docker and Kubernetes, or closely related containerization and cluster computing frameworks.

Nice To Haves

• Candidates with explicit experience working on machine learning orchestration in cloud or HPC environments (using MLFlow, Kubeflow, or similar) will be highly competitive.
• Technical leadership and experience leading development projects and/or teams is desirable but not required.
• Bonus points for demonstrated experience leading efforts in large programs involving multiple cross-functional teams/stakeholders.
• Experience upholding software/production best practices, as well as mentorship/coaching is strongly preferred. A willingness and demonstrated ability in these domains are sufficient.
• Experience with event-driven architectures and implementing event hooks/triggers in API systems.
• Familiarity with webhooks, message queues, and pub/sub systems.
• Ability to design API integrations that enable real-time data updates and notifications.
• Competitive candidates will be agile-minded, demonstrating clear proficiency in iterative software development and prototyping.
• Candidates who’ve worked on Search products, vector databases, knowledge graphs, or other production AI/ML products—particularly with agentic interfaces and integrations—will be highly competitive.

Responsibilities

• Lead the design, development, and implementation of data frameworks, pipelines and services to support data operations for machine learning engineering teams.
• Collaborate with cross-functional teams to identify requirements and provide technical guidance.
• Integrate APIs with systems and platforms for seamless data exchange and enhanced system functionality.
• Produce well-engineered software, including appropriate automated test suites, technical documentation, and necessary operations.
• Boldly explore the bleeding edge of GenAI/agentic tools and frameworks to maximize gains while minimizing failures.
• Ensure consistent application of platform abstractions to ensure quality and consistency with respect to logging and lineage.
• Consult, educate, and coach/mentor on developer best practices and production standards, participate in code reviews and design sessions.
• Adhere to QMS framework and CI/CD best practices and helps to guide improvements to them that improve ways of working.
• Stay up-to-date on emerging technologies, trends, and best practices.
• Identify areas for improvement across the stack.

Benefits

• Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.
• Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level