GSK

Computing Engineer I

GSK

full-time

Posted on:

Location Type: Hybrid

Location: Cambridge • California, Maryland, Massachusetts, Washington • 🇺🇸 United States

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Salary

💰 $88,275 - $147,125 per year

Job Level

Junior

Tech Stack

AnsibleAWSAzureCloudDockerJavaJenkinsKubernetesNode.jsPackerPythonScalaTerraform

About the role

  • Serve as a key engineer for the optimization team and contribute technical expertise to teams in closely aligned technical areas such as DevOps, Cloud and Infrastructure
  • 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 architecture)
  • Participate in scrum team and contribute technical expertise to teams in closely aligned technical areas

Requirements

  • Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
  • 1+ year experience in industry in software engineering in AIML and MLOps
  • Experience using one interpreted and one compiled common industry programming language: e.g., Python, C/C++, Scala, Java, including toolchains for documentation, testing, and operations / observability
  • 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
  • Expertise in modern software development tools / ways of working (e.g. git/GitHub, DevOps tools, metrics / monitoring, …)
  • 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 Vertex AI
  • 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
  • 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
Benefits
  • health care and other insurance benefits (for employee and family)
  • retirement benefits
  • paid holidays
  • vacation
  • paid caregiver/parental and medical leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
PythonC/C++ScalaJavaapplication performance tuningparallel computingdistributed computingAIMLMLOpsML model deployment
Soft skills
technical expertisecollaborationproblem-solvingagile developmentcommunication
Certifications
Bachelor's degreeMaster's degreePhD