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We anticipate the application window for this opening will close on - 29 Oct 2026
Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact.
A Day in the Life
At Medtronic, we are driven by our Mission to alleviate pain, restore health, and extend life for millions of people around the world. Our Customer Experience & Enablement organization plays a critical role in delivering exceptional experiences for customers while supporting the business systems, capabilities, and operations that help bring life-changing therapies to patients.
As the Senior Director, Digital Transformation & AI Strategy, Customer Experience & Enablement, you will define and lead the digital and AI vision for Global Customer Care & Order Operations. Reporting to the Vice President of Customer Care & Order Operations, this strategic leader will accelerate the transformation of customer engagement, service delivery, and order-to-cash operations through artificial intelligence, intelligent automation, digital platforms, and data-driven innovation.
This highly visible enterprise leadership role partners closely with Digital & AI, IT, Data & Analytics, Commercial, Supply Chain, and customer-facing teams to translate strategy into scalable capabilities that improve customer experiences, employee effectiveness, operational performance, and business outcomes.
This strategic transformation leadership role offers location flexibility, including remote work arrangements, based on business needs and candidate qualifications. The role requires up to 25% global travel to Medtronic Operational Headquarters, customer locations, and Medtronic sites worldwide to support strategic initiatives, foster stakeholder engagement, and drive business objectives.
In this role, you will serve as the strategic leader responsible for shaping and executing the long-term AI and digital transformation agenda for Global Customer Care & Order Operations. You will identify opportunities to modernize customer experiences, improve operational efficiency, and create scalable digital capabilities that enable future growth.
Success in this position requires a proven ability to lead enterprise transformation initiatives, influence senior executives, build organizational capability, and deliver measurable business results through innovation and technology adoption.
As the Senior Director, Digital Transformation & AI Strategy, Customer Experience & Enablement, you will:
- Define and execute the global AI and digital transformation strategy for Customer Care & Order Operations, translating business priorities into a multi-year roadmap and investment agenda.
- Reimagine customer and employee experiences through AI-enabled self-service, digital assistants, intelligent workflows, predictive insights, and personalized engagement.
- Lead the simplification, standardization, and automation of end-to-end customer care and order-to-cash processes to improve service, productivity, scalability, and cost to serve.
- Own the business strategy and priorities for customer-facing digital platforms.
- Establish responsible AI governance, performance measures, and value-realization frameworks that connect digital investments to customer, employee, operational, and financial outcomes.
Partner across Digital and AI, IT, Data & Analytics, Commercial, and Supply Chain to deliver secure, integrated capabilities and drive adoption through change leadership and workforce enablement. *
Required Qualifications
To be considered for this role, please ensure these minimum requirements are clearly reflected on your resume:
- Bachelor's degree required.
- Minimum of 15 years of relevant experience with 10+ years of managerial experience; or an advanced degree with a minimum of 13 years of relevant experience and 10+ years of managerial experience.
- Demonstrated experience leading enterprise digital transformation, AI strategy, customer experience, or operational transformation initiatives within a complex global organization.
Proven ability to lead large-scale cross-functional transformation efforts. *
Preferred Qualifications
- Advanced degree in business, technology, engineering, data science, or a related field.
- Deep knowledge of generative AI, conversational AI, machine learning, intelligent automation, workflow orchestration, predictive analytics, and digital product management.
- Experience transforming customer care, contact center, order-to-cash, shared services, or other large-scale customer support operations.
- Track record of translating emerging technology capabilities into measurable customer, employee, operational, and financial value.
- Experience establishing AI governance frameworks, responsible-use practices, performance metrics, and value-realization models.
- Strong strategic, analytical, and problem-solving capabilities.
- Demonstrated success leading organizational change, building capabilities, and driving adoption of new technologies and digital ways of working.
- Excellent executive communication, presentation, and stakeholder management skills.
Experience working within a highly matrixed multinational organization. *
For Baccalaureate degrees earned outside of the United States, a degree that satisfies the requirements of 8 C.F.R. § 214.2(h)(4)(iii)(A) is required.
Physical Job Requirements
The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position.
The physical demands described within the Responsibilities section of this job description are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. For Office Roles: While performing the duties of this job, the employee is regularly required to be independently mobile. The employee is also required to interact with a computer, and communicate with peers and co-workers. Contact your manager or local HR to understand the Work Conditions and Physical requirements that may be specific to each role.
U.S. Work Authorization & Sponsorship
At Medtronic, we are committed to fostering an environment where employees can thrive and make a meaningful impact. In alignment with our enterprise-wide workforce planning approach, U.S. work authorization sponsorship (H-1B, TN, J, etc.) is offered exclusively for Principal-level roles and above, where specialized expertise aligns with long-term business needs. Roles below the Principal level require candidates to possess unrestricted U.S. work authorization at the time of hire and for the duration of employment.
Recruitment Fraud Alert
We are aware of phishing scams targeting job seekers. Please keep the following in mind:
Apply only through official Medtronic channels. All legitimate Medtronic recruiting communications come from approved Medtronic platforms and official @medtronic.com email addresses.
Medtronic will never ask for payment or sensitive personal information (such as bank account or Social Security details) during early stages of the hiring process. Any such requests are not legitimate.
If you receive a suspicious message claiming to be from Medtronic, do not respond, click links, or open attachments.
If you have any questions, concerns regarding the authenticity of a communication alleged to have been made by or on behalf of Medtronic, please contact us immediately at [email protected] .
Benefits & Compensation
Medtronic offers a competitive Salary and flexible Benefits Package
A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage.
Salary ranges for U.S (excl. PR) locations (USD):$212,800.00 - $319,200.00
This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP). The base salary range is applicable across the United States, excluding Puerto Rico. Base pay is based on numerous factors and may vary by job-related knowledge, skills, experience, etc. Compensation and benefits information pertains solely to candidates hired within the United States (local market compensation and benefits will apply for others). The following benefits and additional compensation are available to those regular employees who work 20+ hours per week: Health, Dental and vision insurance , Health Savings Account , Healthcare Flexible Spending Account , Life insurance, Long-term disability leave , Dependent daycare spending account , Tuition assistance/reimbursement , and Simple Steps (global well-being program).
The following benefits and additional compensation are available to all regular employees: Incentive plans, 401(k) plan plus employer contribution and match , Short-term disability , Paid time off , Paid holidays , Employee Stock Purchase Plan , Employee Assistance Program , Non-qualified Retirement Plan Supplement (subject to IRS earning minimums) , and Capital Accumulation Plan (available to Vice Presidents and above, or subject to IRS earning minimums).
Regular employees are those who are not temporary, such as interns. Temporary employees are eligible for paid sick time, as required under applicable state law, and the Employee Stock Purchase Plan. Please note some of the above benefits may not apply to workers in Puerto Rico.
Further details are available at the link below:
Medtronic benefits and compensation plans
It is the policy of Medtronic to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, Medtronic will provide reasonable accommodations for qualified individuals with disabilities.
If you are applying to perform work for Medtronic, Inc. (“Medtronic”) in any position which will involve performing at least two (2) hours of work on average each week within the unincorporated areas of Los Angeles County, you can find here a list of all material job duties of the specific job position which Medtronic reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of a conditional offer of employment. Medtronic will consider for employment qualified job applicants with arrest or conviction records in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Salary Context
This $212K-$319K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Medtronic, 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 $211,950 based on 13,048 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,300. This role's midpoint ($266K) sits 26% above the category median. Disclosed range: $212K to $319K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Medtronic AI Hiring
Medtronic has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Minneapolis, MN, US. Compensation range: $319K - $319K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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