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About This Role
United States \- Remote
JOB ID: R\-242484 LOCATION: United States \- Remote ; Netherlands \- Remote; Portugal \- Remote; Ireland \- Remote WORK LOCATION TYPE: Remote DATE POSTED: Jul. 22, 2026 CATEGORY: Supply Chain SALARY RANGE: 147,467\.35USD \-199,514\.65 USD
Join Amgen’s Mission of Serving Patients
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.
Associate Director of Data Science – Global Supply Chain Digital
What you will do
Let’s do this. Let’s change the world. The Global Supply Chain Digital Team at Amgen is seeking an Associate Director of Data Science to join the cross\-functional Global Supply Chain organization, based either at our Thousand Oaks headquarters or remotely.
In this vital role, you will lead the development and deployment of advanced analytics, AI/ML, GenAI, and digital solutions that transform Global Supply Chain operations and enable reliable delivery of critical medicines to patients worldwide. This role combines strategic leadership with deep technical expertise. In addition to leading advanced data science initiatives, the Associate Director will help establish and scale Amgen’s India\-based digital capability team supporting Global Supply Chain. This includes helping define the organizational structure, operating model, governance, and delivery processes for a team of data scientists and digital developers, while providing ongoing leadership and oversight once the organization is established. We are seeking a Data Science leader with expertise in AI/ML, advanced analytics, digital product development, and modern data architecture, along with a strong understanding of supply chain and manufacturing operations. The successful candidate will collaborate closely with Supply Chain, Operations, Finance, IT, and Digital Technology teams to develop scalable solutions that improve forecasting, planning, inventory optimization, productivity, and operational performance.
Responsibilities may include, but are not limited to:
- Design and deploy AI, GenAI, Agentic, and advanced analytics solutions to transform end\-to\-end Supply Chain operations.
- Lead the development of scalable digital products, analytical applications, and automation capabilities using large and complex datasets.
- Help establish and scale a Global Supply Chain Digital capability team in India, including organizational design, operating model development, governance, and delivery processes.
- Provide leadership and oversight for global teams of data scientists and digital developers across onshore and offshore locations.
- Partner with business leaders, IT, and data engineering teams to deliver robust, scalable, and business\-aligned analytics solutions.
- Develop impactful visualizations and executive\-level insights that support strategic decision\-making and operational transformation.
- Explore and implement emerging technologies and modern data science practices to enhance organizational capabilities.
- Lead productivity analytics initiatives and develop KPIs and performance metrics that drive operational excellence across the global supply chain.
- Mentor and develop Digital/Data Science staff while fostering a culture of innovation, collaboration, and continuous improvement.
Required Skills
- People leadership and organizational management experience
- Experience building and scaling global or offshore technical teams
- Experience developing scalable data science applications for manufacturing or supply chain operations
- Strong expertise in AI/ML, GenAI, advanced analytics, and digital product development
- Proficiency in Python and SQL
- Experience working with large, complex datasets and modern data architecture
- Experience working in Agile teams to deliver digital products
- Experience with data visualization tools such as Spotfire and Matplotlib
- Strong communication, stakeholder management, and cross\-functional collaboration skills
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The dynamic leader we seek is an individual with these qualifications
Basic Qualifications:
- Doctorate degree and 3 years of Engineering, Computer Science, Operations, Analytics, Data Science, or related scientific experience OR
- Master’s degree and 5 years of Engineering, Computer Science, Operations, Analytics, Data Science, or related scientific experience OR
- Bachelor’s degree and 7 years of Engineering, Computer Science, Operations, Analytics, Data Science, or related scientific experience OR
- Associate’s degree and 12 years of Engineering, Computer Science, Operations, Analytics, Data Science, or related scientific experience OR
- High school diploma / GED and 14 years of Engineering, Computer Science, Operations, Analytics, Data Science, or related scientific experience
Preferred Qualifications:
- Passion for data\-driven business transformation and innovation
- Strong strategic thinking and problem\-solving skills
- Ability to manage multiple priorities in a fast\-paced global environment
- Experience working in manufacturing, operations, or supply chain domains
- Experience working within highly collaborative, matrixed, and global organizations
- Demonstrated ability to influence and drive alignment across technical and business teams
What you can expect of us
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.
careers.amgen.com
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
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
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 $147K-$199K 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 Required
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. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($173K) sits 19% below the category median. Disclosed range: $147K to $199K.
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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