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Senior AI/ML Platform Engineer

LinkedIn GSK Cambridge, MA
Not Applicable Posted April 5, 2026 4 variants Job link
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Requirements
  • 6+ years of experience in industry experience in software engineering with a Bachelor’s.
  • 4+ years of experience in industry experience in software engineering with a Master’s.
  • 2+ years of experience in industry and/or academic experience in software engineering with a PhD.
  • 2+ years of experience in AIML engineering, including large-scale model training and production deployment.
  • Experience with delivering projects primarily using Python.
  • Deep knowledge and use of Python programming language including toolchains for documentation, testing, and operations / observability
  • Experience with High-Performance Computing (HPC) at both at software stack as well as hardware level and understanding performance within the HPC systems
Preferred Skills
  • Deep knowledge and use of Python programming language including toolchains for documentation, testing, and operations / observability
  • Deep expertise in modern software development tools / ways of working (e.g. git/GitHub, DevOps tools, metrics / monitoring, …)
  • Deep 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
  • Deep hands-on experience with ML frameworks such as PyTorch or TensorFlow as well as external libraries such as Huggingface and/or Deepspeed.
  • Hands-on experience with frameworks for building agentic AI systems, such as LangGraph, LangChain.
  • Experience with ML application performance tuning and optimization, both for ML training and inference/deployment, including large scale multi-GPU, and/or multi-TPU multi-node distributed training for large models such as LLMs.
  • Experience with CI/CD implementations using git and a common CI/CD stack (e.g., Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab)
  • Experience in ML workflow orchestration and pipelines with tools such as Vertex Pipelines, MLFlow, etc.
  • Experience with MLOps tools and model deployments (including LLMs) such as Kubeflow, Vertex AI Predictions, vLLM, Ollama
  • Deep expertise with Docker, Kubernetes, and the larger CNCF ecosystem including experience with application deployment tools such as Helm
  • Experience with High-Performance Computing (HPC) at both at software stack as well as hardware level and understanding performance within the HPC systems
  • Deep familiarity with the tools, techniques, optimizations in AIML and AIML Platform/MLOps space, including engagement with the open-source community (and potentially making contributions to such tools)
  • Demonstrated excellence with agile software development environments using tools like Jira and Confluence
  • #GSKOnyx
Education
  • (Not required) – Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
  • (Not required) – 6+ years of experience in industry experience in software engineering with a Bachelor’s.
  • (Not required) – 4+ years of experience in industry experience in software engineering with a Master’s.
  • (Not required) – 2+ years of experience in industry and/or academic experience in software engineering with a PhD.