GSK
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 at scale. We 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 DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward creating a next‑generation, metadata‑ and automation‑driven data experience for GSK’s scientists, engineers, and decision‑makers, providing best‑in‑class AI/ML environments, and aggressively engineering our data at scale to unlock its value in real‑time.
We’re looking for a highly skilled
Senior AIML Optimization Engineer
to help us make this vision a reality.
Key Responsibilities:
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.
Lead design of major optimization software components of the Compute and AIML Platforms, contribute to development of production code, and participate in design and PR reviews.
Be accountable for delivery of scalable solutions to the Compute and AIML Platforms that support the entire application lifecycle, with particular focus on performance at scale.
Partner with AIML and Compute platform teams and scientific users to help optimize and scale scientific workflows using deep knowledge of software and underlying infrastructure (networking, storage, GPU architectures).
Participate in or lead scrum teams and contribute technical expertise to closely aligned technical areas.
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 during change.
Act as a standard bearer for proper ways of working and engineering discipline, including CI/CD best practices, and proactively spearhead improvement within the engineering area.
Why you? Basic Qualifications:
Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
6+ years of experience as a Computer Engineer, or 4+ years with a Master’s, or 2+ years with a 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 industry programming language (e.g., Python, C/C++, Scala, Java) with toolchains for documentation, testing, and operations/observability.
Deep experience with application performance tuning and optimization 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, 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 (e.g., Google Batch, Vertex AI).
Expert understanding of AIML training optimization, including distributed multi‑node training best practices and practical experience accelerating training jobs.
Understanding of ML model deployment strategies, including agent systems and scalable LLM inference systems deployed in multi‑GPU, multi‑node environments.
Experience with CI/CD implementations using git and common CI/CD stacks (e.g., 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 application build 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.
Salary & Benefits: If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges from $136,950 to $228,250, with annual bonus and participation in a share‑based long‑term incentive program. Benefits include health care and other insurance for employees and families, retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK? GSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, focusing on respiratory, immunology and inflammation, oncology, HIV, and infectious diseases. Our culture emphasizes ambition for patients, accountability for impact, and doing the right thing.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities, contact us at HR.AmericasSC-CS@gsk.com where you can also request a call.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information, military service or any basis prohibited under federal, state or local law.
Important notice to Employment businesses/Agencies: GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The absence of such authorization may result in actions being considered performed without consent or contractual agreement with GSK. GSK shall therefore not be liable for any fees arising from such actions or referrals by employment businesses/agencies.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenditures on your behalf in the event you are afforded an interview for employment. For more information, visit the Centers for Medicare and Medicaid Services website at https://openpaymentsdata.cms.gov/.
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Onyx is a full‑stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward creating a next‑generation, metadata‑ and automation‑driven data experience for GSK’s scientists, engineers, and decision‑makers, providing best‑in‑class AI/ML environments, and aggressively engineering our data at scale to unlock its value in real‑time.
We’re looking for a highly skilled
Senior AIML Optimization Engineer
to help us make this vision a reality.
Key Responsibilities:
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.
Lead design of major optimization software components of the Compute and AIML Platforms, contribute to development of production code, and participate in design and PR reviews.
Be accountable for delivery of scalable solutions to the Compute and AIML Platforms that support the entire application lifecycle, with particular focus on performance at scale.
Partner with AIML and Compute platform teams and scientific users to help optimize and scale scientific workflows using deep knowledge of software and underlying infrastructure (networking, storage, GPU architectures).
Participate in or lead scrum teams and contribute technical expertise to closely aligned technical areas.
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 during change.
Act as a standard bearer for proper ways of working and engineering discipline, including CI/CD best practices, and proactively spearhead improvement within the engineering area.
Why you? Basic Qualifications:
Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.
6+ years of experience as a Computer Engineer, or 4+ years with a Master’s, or 2+ years with a 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 industry programming language (e.g., Python, C/C++, Scala, Java) with toolchains for documentation, testing, and operations/observability.
Deep experience with application performance tuning and optimization 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, 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 (e.g., Google Batch, Vertex AI).
Expert understanding of AIML training optimization, including distributed multi‑node training best practices and practical experience accelerating training jobs.
Understanding of ML model deployment strategies, including agent systems and scalable LLM inference systems deployed in multi‑GPU, multi‑node environments.
Experience with CI/CD implementations using git and common CI/CD stacks (e.g., 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 application build 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.
Salary & Benefits: If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges from $136,950 to $228,250, with annual bonus and participation in a share‑based long‑term incentive program. Benefits include health care and other insurance for employees and families, retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK? GSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, focusing on respiratory, immunology and inflammation, oncology, HIV, and infectious diseases. Our culture emphasizes ambition for patients, accountability for impact, and doing the right thing.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities, contact us at HR.AmericasSC-CS@gsk.com where you can also request a call.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information, military service or any basis prohibited under federal, state or local law.
Important notice to Employment businesses/Agencies: GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The absence of such authorization may result in actions being considered performed without consent or contractual agreement with GSK. GSK shall therefore not be liable for any fees arising from such actions or referrals by employment businesses/agencies.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenditures on your behalf in the event you are afforded an interview for employment. For more information, visit the Centers for Medicare and Medicaid Services website at https://openpaymentsdata.cms.gov/.
#J-18808-Ljbffr