Senior AIML Optimization Engineer

Senior AIML Optimization Engineer – GSK

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Site Name:
Seattle Sixth Ave, Cambridge 300 Technology Square
Posted Date:
Dec 10 2025

The Onyx Research Data Tech organization is GSK’s research data ecosystem that brings together, analyzes, and powers the exploration of data  partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. Our goal is to ensure scientists have the right data and insights when they need them to give them a better starting point for and accelerate medical discovery, ultimately helping 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 Dev Ops, data/metadata/knowledge platforms, and AI/ML and analysis platforms. Our focus is on:

• 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.

The AIML & Scientific Computing Optimization team is focused on optimizing first‑in‑class compute and AIML platforms that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking. The platform is metadata‑forward and CI/CD‑driven, covering interactive development (notebooks), large‑scale batch processing, observability and production application deployments.

• Serve as a key engineer for the optimization team and contribute technical expertise to closely aligned technical areas such as Dev Ops, 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 design reviews and PR reviews.
• Be accountable for delivery of scalable solutions that support the entire application lifecycle, with particular focus on performance at scale.
• Partner with AIML and compute platform teams and scientific users to optimize and scale scientific workflows by leveraging deep understanding of software and underlying infrastructure (networking, storage, GPU architectures, etc.).
• Participate or lead scrum teams and contribute technical expertise to closely aligned teams.
• Design innovative strategies and ways of working to create a better environment for end users and construct a coordinated, stepwise plan to bring others along with the change curve.
• Act as the standard bearer for proper ways of working and engineering discipline, including CI/CD best practices, and proactively spearhead improvements within the engineering area.

• Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
• 6+ years of experience with a Bachelor’s, 4+ years with a Master’s, and 2+ years with a Ph.D. using specialized knowledge in cloud computing, scalable parallel computing paradigms, software engineering, and CI/CD.
• 2+ years of experience in AIML engineering, including large‑scale model training and production deployment.

• Deep experience using at least one interpreted and one compiled common industry programming language (e.g., Python, C/C++, Scala, Java) including tool chains for documentation, testing, and operations/observability.
• Deep experience with application performance tuning and optimization, including in parallel and distributed computing paradigms and communication libraries such as MPI, OpenMP, Gloo, and a deep understanding of underlying systems (hardware, networks, storage).
• Deep expertise in modern software development tools and ways of working (e.g., git/Git Hub, Dev Ops…