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 engineering discipline, including CI/CD best practices and proactively spearhead improvement within their engineering area
• Serve as a technical thought leader and champion: e.g., speak at industry events, promote GSK as an attractive place to build a career and thrive as an AIML engineer, act as a key knowledge holder for the Onyx organization

Why You?

Basic Qualifications:

• Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
•  8+ years of experience using specialized knowledge in machine learning, data structures, algorithms, parallel computing paradigms, software operations, cloud computing with Bachelor’s.
• 6+ years of experience using specialized knowledge in machine learning, data structures, algorithms, parallel computing paradigms, software operations, cloud computing with Master’s.
• 4+ years of experience using specialized knowledge in machine learning, data structures, algorithms, parallel computing paradigms, software operations, cloud computing with a PhD.
• At least 2 years of experience with recruiting, managing, and developing engineers or other deeply technical contributors.

Preferred Qualifications:

• Deep knowledge and use of Python programming language including toolchains for documentation, testing, and operations / observability
• Deep expertise in modern software development tools / ways of working (e.g. git/GitHub, devops tools, metrics / monitoring, …)
• Deep cloud expertise (e.g., AWS, Google Cloud, Azure), including infrastructure-as-code tools (Terraform, Ansible, Packer, …) and scalable cloud compute technologies, such as Google Batch and VertexAI
• Deep hands-on experience with ML frameworks such as PyTorch or TensorFlow as well as external libraries such as Huggingface and/or Deepspeed.
• Hands-on experience with frameworks for building agentic AI systems, such as Langgraph, Langchain
• Experience with ML application performance tuning and optimization, both for ML training and inference/deployment, including large scale multi-GPU, and/or multi-TPU multi-node distributed training for large models such as LLMs. 
• Experience with CI/CD implementations using git and a common CI/CD stack (e.g., Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab)
• Experience in ML workflow orchestration and pipelines with tools such as Vertex Pipelines, MLFlow, etc.
• Experience with MLOps tools and model deployments (including LLMs) such as Kubeflow, Vertex AI Predictions, vLLM, Ollama
• Deep expertise with Docker, Kubernetes, and the larger CNCF ecosystem including experience with application deployment tools such as Helm
• Experience with High-Performance Computing (HPC) at both at software stack as well as hardware level and understanding performance within the HPC systems
• Deep familiarity with the tools, techniques, optimizations in AIML and AIML Platform/MLOps space, including engagement with the open-source community (and potentially making contributions to such tools)
• Demonstrated excellence with agile software development environments using tools like Jira and Confluence
• Experience with establishing software engineering ways of working and best practices for a team (whether informally or as formal SOPs etc.)
• Experience recruiting top engineering talent
• Experience with agile planning and execution processes for software delivery

Purpose of Onyx

#GSKOnyx

#LI-GSK

The annual base salary for new hires in this position ranges from $188,100 to $313,500 taking into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. 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.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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