Director of AIML & Scientific Computing Optimization, GSK
$161.3-268.8k
Plus annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role
2-3 days a week in office
Building a cutting-edge digital and tech team.
Job no longer available
Building a cutting-edge digital and tech team.
1001+ employees
Job no longer available
$161.3-268.8k
Plus annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role
2-3 days a week in office
1001+ employees
Company mission
At GSK, we use technology to deliver what matters most, better and faster. Whether it’s life-saving medicines or life-enhancing products, Tech at GSK helps scale and accelerate our expertise.
Role
Who you are
- Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline
- 8+ years of experience using specialized knowledge in cloud computing, scalable parallel computing paradigms, software engineering, CI/CD with Bachelor’s
- 6+ years of experience using specialized knowledge in cloud computing, scalable parallel computing paradigms, software engineering, CI/CD with Master’s
- 4+ years of experience using specialized knowledge in cloud computing, scalable parallel computing paradigms, software engineering, CI/CD with a PhD
- At least 2 years of experience with recruiting, managing, and developing engineers or other deeply technical contributors
Desirable
- Deep experience using at least one interpreted and one compiled common industry programming language: e.g., Python, C/C++, Scala, Java, including toolchains for documentation, testing, and operations / observability
- Hands-on experience with application performance tuning and optimization, including in parallel and distributed computing paradigms and communication libraries such as MPI, OpenMP, Gloo, including deep understanding of the underlying systems (hardware, networks, storage) and their impact on application performance
- Expert understanding of AIML training optimization, including distributed multi-node training best practices and associated tools and libraries as well as hands-on practical experience in accelerating training jobs
- Understanding of ML model deployment strategies, including agent systems as well as scalable LLM model inference systems deployed in multi-GPU, multi-node environments
- Deep expertise in modern software development tools / ways of working (e.g. git/GitHub, DevOps tools, metrics / monitoring, …)
- Cloud experience (e.g., AWS, Google Cloud, Azure), including infrastructure-as-code and relevant tools and libraries such as Terraform, Ansible, and Packer
- Experience with CI/CD implementations using git and a common CI/CD stack (e.g., Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab)
- Experience with Docker, Kubernetes, and the larger CNCF ecosystem including experience with application deployment tools such as Helm
- Experience with low level application builds tools (make, CMake) and understanding of optimization at the build and compile level
- Demonstrated excellence with agile software development environments using tools like Jira and Confluence
- Deep familiarity with the tools, techniques, optimizations in high-performance applications space, including engagement with the open-source community (and potentially making contributions to such tools)
- 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
What the job involves
- A Director of AIML & Scientific Computing Optimization is a deeply technical leader
- They consistently deliver major compute and AIML platform features and solutions with cross-organizational impact and value
- They are recognized as expert in software engineering, scientific computing, and/or AIML with deep understanding of performance and optimization, 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
- This role is responsible for building and leading a team of world-class software engineers focused on optimizing a best-in-class Compute and AIML Platforms at scale, quality, and cost
- The Director of AIML & Scientific Computing Optimization 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 AI/ML Platform team, Compute Platform team, Data and Infrastructure Engineering, 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
- Build, lead, develop, and retain world-class software engineers
- Serve as a top expert for the optimization team, and contribute technical expertise to teams in closely aligned technical areas such as DevOps, Cloud and Infrastructure
- Lead design of major optimization software components of the Compute and AIML Platforms, contribute to development of production code and participate in both design reviews and PR reviews
- Accountable for delivery of scalable solutions to the Compute and AIML Platforms that supports the entire application lifecycle (interactive development and explorations/analysis, scalable batch processing, application deployment) with particular focus on performance at scale
- Partner with both AIML and Compute platform teams as well as scientific users to help optimize and scale scientific workflows by utilizing deep understanding of both software as well as underlying infrastructure (networking, storage, GPU architectures, …)
- Direct scrum team leads, and contribute technical expertise to teams in closely aligned technical areas
- Able to design innovative strategy and way 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 a Platform engineer, act as a key knowledge holder for the Onyx organization
Salary benchmarks
Our take
GSK Tech is set to build a suite of next-generation platforms for data- and prediction-driven drug discovery in support of GSK's Research and AI/ML organizations, and an industry-leading data engineering function in support of AI/ML and Genomic Sciences.
GSK’s ambitions go far past the data lake: they’re building a comprehensive data and machine learning ecosystem that can speak to the customers in their own scientific and technical language and semantics. Enabled by GSK Knowledge Graph, powered by machine learning, and underpinned by natural language processing, GSK's vision is for accessibility to data (and, importantly, the knowledge it represents). GSK wants to increase this tenfold, taking mere moments to find, access, and integrate the right information.
The creation of GSK Tech shows GSK's commitment to making a major investment in changing how we think about data in the research space, and levelling up the data experience for GSK's researchers, scientists, computational scientists, AI/ML Engineers, and ultimately decision-makers. As of 2024, GSK is putting more energy into its Cyber Security features, thus widening its market reach.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- An annual bonus based on company performance
- Access to healthcare and wellbeing programmes, pension plan membership, savings programmes, time off and childcare support
- Employee recognition programmes which reward exceptional achievements
- Long term incentives through share ownership link your rewards to our longer term performance
- Coaching, mentoring and formal training programmes
- Plenty of opportunities for open conversations with people who can help to shape your career
- A range of health and wellbeing programmes and support services to help employees understand how to feel healthier, happier and more energised at work and at home
Company HQ
Brentford, UK
Leadership
Luke Miels
(CEO)Luke became CEO on Jan 1, 2026, after serving as CEO designate since Sept 2025. He joined GSK in 2017 as Chief Commercial Officer, responsible for our commercial portfolio of medicines and vaccines.
Shobie Ramakrishnan
(Chief Digital and Technology Officer)Has a broad experience in biotech and hi-tech companies. Has led Digital and Technology for GSK’s Global Commercial organisation, transforming the company’s capabilities in digital, data & analytics.
Michael Elmore
(SVP & Global Chief Information Security Officer)Experienced in building and leading tech teams across cyber security, IT infrastructure, application development, and more. A trusted advisor to VCs and startups focusing on cybersecurity advancements.
Shubha Chaudhari
(SVP, Development Digital & Tech)Previously worked at Novartis in several roles, including Head of Clinical Informatics, Global Head of Development Informatics, and Head of Digital Transformation.
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