Director, AIML Platform Engineering

The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.

Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:​

• Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”.
• Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent.
• Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time.

Our AI/ML Platform Engineering team is building a first-in-class platform of tools and services with abstractions that encompass Cloud and High-Performance Computing. This metadata forward, CI/CD-driven platform represents and enables the entire ML lifecycle including model development, large-scale training and evaluation, MLOps/Observability and scalable production deployments. The team sets the standards for software engineering across Onyx, AIML and beyond with the goal of decreasing development and iteration time and raising the quality bar on engineering across AI/ML teams and products.

A Director of AIML Platform Engineering is a deeply technical leader. They consistently deliver major AIML platform features and solutions with cross-organizational impact and value. They are a recognized expert in AI/ML Platforms and MLOps within the Onyx team, across R&D Digital & Tech, and even externally. They can work closely with -- and have strong technical knowledge of – underlying platform dependencies such as DevOps, Infrastructure and Cloud and can enable collaborations and help drive the requirements across other Onyx engineering teams that results in improved performance and better user experience. They support and maintain the core AIML Platform capabilities using a site reliability approach through monitoring, auditing, and alerting, which trigger automated corrective actions and processes.

This role is responsible for building and leading a team of world-class AIML Platform engineers focused on building a world-class AIML Platform at scale and quality. The Director of AIML Platform Engineering will support the Sr. Director of Computing, Analysis, and AI/ML Platforms in building a strong culture of accountability and ownership in their team, as well as instilling best-in-class engineering practices (e.g. testing, code reviews, DevOps-forward ways of working). They work in close partnership with Compute Platform team, Data Engineering, Cloud Infrastructure and DevOps, Product Management, Portfolio Management, and other engineering functions to ensure close alignment with customers and with engineering teams both upstream and downstream of their work.

Key Responsibilities:

• Build, lead, develop, and retain world-class AIML Platform and MLOps engineers
• Serve as a top architect for the AIML platform, and contribute technical expertise to teams in closely aligned technical areas such as GenAI Platform, DevOps, Compute and Cloud
• Lead design of major software components of the AIML Platform and contribute to development of production code in Python and participate in both design reviews and PR reviews
• Accountable for delivery of a scalable AIML Platform that supports the entire ML lifecycle (development, training, MLOps/deployment/inference) with particular focus on usability, reproducibility and performance at scale
• Partner with leads of AIML and Onyx engineering functions to architect an engagement model and optimal ways of working with the Product Management teams
• Integrate with DataOps, and Data Engineering products for best performance and ease of use in ML training at scale
• Direct scrum team leads, and contribute technical expertise to teams in closely aligned technical areas to soundly execute the AIML platform architectural vision
• Able to design innovative strategy and ways of working to create a better environment for the end users, and able to construct a coordinated, stepwise plan to bring others along with the change curve
• Standard bearer for proper ways of working and en