AIML OptimizationEngineer
Listed on 2025-12-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer
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 which has the capability to bring together, analyze, and power the exploration of data 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 Dev Ops, 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.
At GSK we see a world in which advanced applications of 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 AI and Machine Learning.
We're looking for a highly skilled AI/ML Optimization Engineer to help us make this vision a reality.
Our AI/ML & Scientific Computing Optimization team is focused on optimizing first‑in‑class Compute and AI/ML platforms that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking over abstractions that encompass Cloud and High‑Performance Computing. This metadata‑forward, CI/CD‑driven platform represents and enables the entire application and analysis lifecycle including interactive development and explorations (notebooks), large‑scale batch processing, observability and production application deployments.
The optimization team's focus is on maximizing scale and performance of all aspects of the platforms.
The AI/ML & Scientific Computing Optimization 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 from day one, supporting individuals in dedicating 20% of their time towards personal development.
Key Responsibilities- Serve as a key engineer for the optimization team and contribute technical expertise to teams in closely aligned technical areas such as Dev Ops, Cloud, and Infrastructure.
- Accountable for delivery of scalable solutions to the Compute and AI/ML Platforms that support the entire application lifecycle (interactive development and explorations/analysis, scalable batch processing, application deployment) with particular focus on performance at scale.
- Partner with both AI/ML 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 architecture).
- Participate in scrum team and contribute technical expertise to teams in closely aligned technical areas.
- Bachelor's, Master's or PhD degree in Computer Science, Software Engineering, or related discipline.
- 1+ year experience in industry in software engineering in AI/ML and MLOps.
- Experience using one interpreted and one compiled common industry programming language: e.g., Python, C/C++, Scala, Java, including tool chains for documentation, testing, and operations /…
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