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Sr. Scientist – AI/ML Governance & Operations

Amgen

Sr. Scientist – AI/ML Governance & Operations

full-timePosted: Jul 29, 2026Updated: Aug 28, 2026India - Hyderabad

Job Description

Career CategoryResearchJob DescriptionHOW MIGHT YOU DEFY IMAGINATION?If you feel like you're part of something bigger, it's because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world's leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It's time for a career you can be proud of.Sr. Scientist – AI/ML Governance & Operations (Large Molecule Discovery Informatics)LiveWhat you will doIn this vital role, the LM ML Standards & Governance Specialist will play a key part in establishing the foundational standards, governance processes, and operational practices required to scale AI and machine learning capabilities across Large Molecule Discovery (LMD). This role will help ensure that machine learning assets, code repositories, documentation, data dependencies, and deployment practices are reproducible, secure, compliant, and aligned with enterprise requirements.Working closely with AI/ML scientists, software engineers, data engineers, informatics teams, and enterprise technology partners, this individual will help define and implement governance frameworks that support the responsible development, deployment, and maintenance of AI-enabled scientific solutions. The role will serve as a bridge between scientific innovation and operational rigor, ensuring that emerging AI capabilities can be effectively maintained, audited, and scaled across research workflows.This position is well suited for someone who enjoys building structure around complex technical ecosystems and has experience supporting machine learning operations, technical governance, software lifecycle management, or scientific platform administration.Core responsibilities include:Establish standards for machine learning code, documentation, model artifacts, and supporting technical assetsDefine and implement best practices for model lifecycle management, version control, release management, and reproducibilityPartner with scientists to ensure AI workflows can be validated, reproduced, and maintained over timeSupport management of shared repositories, technical assets, and documentation systemsCollaborate with technology teams to implement scalable governance, repository, and lifecycle management practicesAlign AI development practices with enterprise security, compliance, and technology expectationsTranslate scientific requirements into operational standards that enable sustainable AI adoptionDrive consistency and reuse of AI assets across the Large Molecule Discovery organizationWinWhat we expect of youBasic Qualifications:Doctorate degree PhDOrMaster’s degree and 8+ years of directly related experienceOrBachelor’s degree and 10+ years of directly related experiencePreferred Qualifications:Experience supporting machine learning platforms, MLOps environments, or AI governance programsUnderstanding of machine learning lifecycle management and model deployment practicesExperience implementing standards for model documentation, validation, and reproducibilityFamiliarity with source control systems, CI/CD pipelines, and software development lifecycle practicesExperience working in biotechnology, pharmaceutical, life sciences, or research environmentsStrong organizational, documentation, and stakeholder management skillsAbility to balance governance requirements with practical scientific needsThriveWhat you can expect of usAs we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.A discretionary annual bonus program, or for field sales representatives, a sales-based incentive planStock-based long-term incentivesAward-winning time-off plans and bi-annual company-wide shutdownsFlexible work models, including remote work arrangements, where possibleApply nowfor a career that defies imaginationObjects in your future are closer than they appear. Join us.careers.amgen.comApplication deadlineAmgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation..

Locations

  • India - Hyderabad

Skills Required

  • source control systemsintermediate

Required Qualifications

  • Doctorate degree PhD (degree)
  • Master’s degree and 8+ years of directly related experience (experience, 8 years)
  • Bachelor’s degree and 10+ years of directly related experience (experience, 10 years)

Preferred Qualifications

  • Experience supporting machine learning platforms, MLOps environments, or AI governance programs (experience)
  • Understanding of machine learning lifecycle management and model deployment practices (experience)
  • Experience implementing standards for model documentation, validation, and reproducibility (experience)
  • Familiarity with source control systems, CI/CD pipelines, and software development lifecycle practices (experience)
  • Experience working in biotechnology, pharmaceutical, life sciences, or research environments (experience)
  • Strong organizational, documentation, and stakeholder management skills (experience)
  • Ability to balance governance requirements with practical scientific needs (experience)

Responsibilities

  • In this vital role, the LM ML Standards & Governance Specialist will play a key part in establishing the foundational standards, governance processes, and operational practices required to scale AI and machine learning capabilities across Large Molecule Discovery (LMD). This role will help ensure that machine learning assets, code repositories, documentation, data dependencies, and deployment practices are reproducible, secure, compliant, and aligned with enterprise requirements.
  • Working closely with AI/ML scientists, software engineers, data engineers, informatics teams, and enterprise technology partners, this individual will help define and implement governance frameworks that support the responsible development, deployment, and maintenance of AI-enabled scientific solutions. The role will serve as a bridge between scientific innovation and operational rigor, ensuring that emerging AI capabilities can be effectively maintained, audited, and scaled across research workflows.
  • This position is well suited for someone who enjoys building structure around complex technical ecosystems and has experience supporting machine learning operations, technical governance, software lifecycle management, or scientific platform administration.Core responsibilities include:
  • Establish standards for machine learning code, documentation, model artifacts, and supporting technical assets
  • Define and implement best practices for model lifecycle management, version control, release management, and reproducibility
  • Partner with scientists to ensure AI workflows can be validated, reproduced, and maintained over time
  • Support management of shared repositories, technical assets, and documentation systems
  • Collaborate with technology teams to implement scalable governance, repository, and lifecycle management practices
  • Align AI development practices with enterprise security, compliance, and technology expectations
  • Translate scientific requirements into operational standards that enable sustainable AI adoption
  • Drive consistency and reuse of AI assets across the Large Molecule Discovery organization

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