Sr. Scientist – AI/ML Governance & Operations
About this opportunity
Career Category
Research
Job Description
HOW 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)
Live
What you will do
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
Win
What we expect of you
Basic Qualifications:
Doctorate degree PhD
Or
Master’s degree and 8+ years of directly related experience
Or
Bachelor’s degree and 10+ years of directly related experience
Preferred Qualifications:
Experience supporting machine learning platforms, MLOps environments, or AI governance programs
Understanding of machine learning lifecycle management and model deployment practices
Experience implementing standards for model documentation, validation, and reproducibility
Familiarity with source control systems, CI/CD pipelines, and software development lifecycle practices
Experience working in biotechnology, pharmaceutical, life sciences, or research environments
Strong organizational, documentation, and stakeholder management skills
Ability to balance governance requirements with practical scientific needs
Thrive
What you can expect of us
As 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 plan
Stock-based long-term incentives
Award-winning time-off plans and bi-annual company-wide shutdowns
Flexible work models, including remote work arrangements, where possible
Apply now
for a career that defies imagination
Objects in your future are closer than they appear. Join us.
careers.amgen.com
Application deadline
Amgen 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.
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Job details
How this role compares
Computed from every other active Drug Discovery & Preclinical Research role in our database, not just this employer's listings.
We currently track 188 comparable Senior Drug Discovery & Preclinical Research roles across 30 biopharma companies.
Salary context
62 of 188 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 188 comparable roles
+ 6 more countries
Seniority mix
188 of 188 peers have a known seniority level
Therapeutic area mix
29 of 188 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.