Senior AIML Optimization Engineer

7 days ago


Seattle, United States GlaxoSmithKline Full time

Overview Onyx Research Data Tech is part of GSK’s Research data ecosystem, bringing together science, data and AI/ML to accelerate medical discovery. Key Responsibilities Serve as a key engineer for the optimization team and contribute technical expertise to 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 design reviews and PR reviews. Accountable for delivery of scalable solutions to the Compute and AIML Platforms that support the entire application lifecycle, focusing on performance at scale. Partner with AIML and Compute platform teams and scientific users to optimize and scale scientific workflows using deep understanding of software and underlying infrastructure. Participate or lead scrum team and contribute technical expertise to closely aligned technical areas. Design innovative strategy and ways of working to create a better environment for end users and construct a coordinated stepwise plan to bring others along. Standard bearer for proper ways of working and engineering discipline, including CI/CD best practices and proactively spearhead improvement within the engineering area. Basic Qualifications Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering or related discipline. 6+ years of experience (Bachelor’s), 4+ years with Masters, 2+ years with PhD 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. Preferred Qualifications Deep experience using at least one interpreted and one compiled common industry programming language (Python, C/C++, Scala, Java) and associated toolchains. Deep experience with application performance tuning and optimization in parallel and distributed computing paradigms and communication libraries (MPI, OpenMP, Gloo) and systems knowledge. Deep expertise in modern software development tools and ways of working (git, DevOps tools, metrics, monitoring). Deep cloud expertise (AWS, Google Cloud, Azure) and infrastructure‑as‑code tools (Terraform, Ansible, Packer). Expert understanding of AIML training optimization, distributed multi‑node training best practices and hands‑on experience accelerating training jobs. Understanding of ML model deployment strategies, agent systems and scalable LLM inference systems deployed in multi‑GPU, multi‑node environments. Experience with CI/CD implementations using git and a common CI/CD stack (Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab). Experience with Docker, Kubernetes and the larger CNCF ecosystem, including application deployment tools such as Helm. Experience with low‑level build tools (make, CMake) and understanding optimization at build and compile level. Demonstrated excellence with agile software development environments using tools like Jira and Confluence. GSK is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex, pregnancy, gender identity or sexual orientation, parental status, national origin, age, disability, genetic information, military service or any basis prohibited under federal, state or local law. #J-18808-Ljbffr



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