Interested in this AI/ML Engineer role at Amgen?
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United States \- Remote
JOB ID: R\-251391 LOCATION: United States \- Remote WORK LOCATION TYPE: Remote DATE POSTED: Aug. 07, 2026 CATEGORY: Information Systems SALARY RANGE: 121,527\.05USD \-164,418\.95 USD
Join Amgen’s Mission of Serving Patients
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At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity\-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award\-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
AI Literacy Manager
What you will do
Let’s do this. Let’s change the world. In this vital role you will be responsible for AI Literacy program management, learning operations and go\-to\-market product delivery. This incudes managing AI Literacy programs, developing trainings, and increasing AI fluency and readiness, measured via engagement metrics, feedback, and adoption rates.
ABOUT THE ROLE
The Manager, AI Literacy will lead complex, cross\-functional enterprise efforts to ensure Amgen colleagues can understand foundational AI concepts, apply AI responsibly and collaborate with AI meaningfully in their day\-to\-day work.
You will be responsible for leading enterprise\-wide programs and moments that inspire and scale AI literacy and adoption globally. Collaborate with Corporate Affairs, Responsible AI Literacy, functional Learning \& Performance leaders and technical teams to continuously evolve existing AI literacy efforts focused on AI fundamentals, applying AI responsibly and human\-AI collaboration.
Responsibilities:
- AI Literacy: Plan and deliver AI literacy initiatives that reach employees at all levels across Amgen, with an initial focus on certification programs and large\-scale social learning events.
- Cross\-Functional Collaboration: Collaborate with product, technology, communications and responsible AI teams to plan, coordinate and implement AI literacy programs, ensuring that AI learning initiatives adhere to enterprise guidelines and responsible AI policies.
- Change Enablement: Develop cultural transformation initiatives for engagement strategies that drive organizational alignment on AI initiatives. Partner with functions to identify role\-specific workflow opportunities and help teams integrate AI into business processes, driving measurable improvements in productivity, quality, and decision\-making.
- Education \& Engagement Program Delivery: Implement tailored education programs to build AI fluency across all levels of the organization, ensuring teams are equipped to use AI effectively. Develop tailored material and training modules for leaders and partners
- Organize and deliver high\-impact events (e.g., AI Symposiums, Digital Learning Days, Hackathons) to foster community engagement. Collaborate with Corporate Affairs to create marketing material and campaigns for these events.
- Stakeholder Engagement: Lead stakeholder mapping, management and inclusion. Create enterprise ready content to ensure cohesive messaging and clear articulation of AI's value across the organization.
- Performance Monitoring \& Reporting: Track and report on the effectiveness of AI learning programs and GTM initiatives. Define and monitor adoption, engagement, capability, and business impact metrics to assess effectiveness and continuously improve programs.
- AI expertise: Understand when and how to apply generative AI to produce better outcomes, increase efficiency and enhance your cognitive capacity and judgement.
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The technology professional we seek is an educator with these qualifications.
Basic Qualifications:
Doctorate degree with 5 years of AI or technology education or Go\-to\-Market experience
OR
Master’s degree and 8 years of AI or technology education or Go\-to\-Market experience
Preferred Qualifications:
- Project and Change Management: 5\+ years of experience leading large\-scale AI or technology transformation programs in large, complex Fortune 500 environments. Record of building strong partnerships with cross\-functional teams and managing diverse workloads to meet deadlines. Agile, PMP, and/or Prosci certifications are preferred.
- Learning \& Development: Consistent track record of executing successful L\&D or GTM technology programs, preferably in a biopharma, technology, or AI\-focused environment. Background in adult learning theory or learning experience design for technology\-related skills.
- AI Acumen: Comfortable using generative AI tools like ChatGPT, Copilot and Lovable to improve business results. Know how to avoid AI slop and continue to think for yourself while improving results with AI. Hands\-on technical ability to build Custom GPTs, Workspace agents and other automations. Optimistic and empathetic approach to AI enablement. Understanding of AI\-focused solutions and digital transformation trends, particularly in life sciences.
- Expert Communication Skills: Demonstrable ability to translate technical concepts for non\-technical stakeholders and communicate effectively to both technical and non\-technical audiences to inspire and scale adoption. Experience producing executive level content and reporting.
- Independent and Collaborative Working Style: Ability to work autonomously with minimal guidance and know when to seek input, combined with a collaborative approach to obtain alignment and support project goals.
- Leadership Skills: Strong leadership and team management skills with experience managing cross\-functional teams for GTM and technical education programs.
- Innovation mindset and ability to navigate ambiguity and operate in startup mode in a large, complex organization.
Nice\-to\-Have
- Background in AI/software development or IT delivery
- Familiarity with AI\&D product lifecycle and go\-to\-market strategies.
- Familiarity with enterprise learning ecosystems, layered literacy models, role\-based enablement, or function\-led training coordination
- Experience developing or deploying AI\-enabled enablement tools, such as chatbots, knowledge assistants, retrieval\-based guidance tools, workflow copilots, or other interactive guidance mechanisms
- Experience with human\-centered design, service design, product management, UX research, or responsible AI
What you can expect of us
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As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well\-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.
The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.
In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:
- A 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
- Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.
and make a lasting impact with the Amgen team.
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careers.amgen.com
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In any materials you submit, you may redact or remove age\-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
Application deadline
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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.
Sponsorship
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Sponsorship for this role is not guaranteed.
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
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.
Salary Context
This $121K-$164K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Amgen, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($142K) sits 33% below the category median. Disclosed range: $121K to $164K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Amgen AI Hiring
Amgen has 14 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Remote, US, Lisbon, ME, US. Compensation range: $139K - $244K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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