Sr. Director, Data & AI Program Portfolio Management

$209K - $314K Minneapolis, MN, US Senior AI/ML Engineer

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About This Role

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We anticipate the application window for this opening will close on \- 11 Aug 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

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At Medtronic, you can begin a life\-long career of exploration and innovation while helping champion healthcare access and equity for all. You'll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world.

As the Senior Director, Data \& AI Program Portfolio, you will serve as a key member of the Data \& AI leadership team and be accountable for establishing and leading the operating system that drives portfolio governance, business operations, financial discipline, organizational effectiveness, and service excellence across the Data \& AI organization. This highly visible leadership role will ensure investments translate into measurable business outcomes while strengthening execution, operational rigor, adoption, and value realization across a broad and strategic technology portfolio.

You will partner across Data \& AI, Enterprise Architecture, IT, Finance, HR, Strategic Program Management Office (SPMO), IT Business Partners, and enterprise stakeholders to deliver transparency, governance, and execution excellence while driving operational performance, cost efficiency, and service reliability.

This role follows Medtronic's flexible workplace model and requires a minimum of four days per week onsite at one of Medtronic's major U.S. operational hubs, including Minneapolis, MN; Lafayette, CO; Mansfield, MA; or North Haven, CT. As a highly collaborative leadership position driving enterprise\-wide Data \& AI strategy and transformation, regular in\-person engagement with business leaders, technology teams, and key stakeholders is essential to foster innovation, accelerate decision\-making, and deliver impactful business outcomes across the organization.

In this role, you will:

  • Lead the Data \& AI operating model, overseeing portfolio intake, prioritization, governance, execution oversight, and business operations to ensure strategic alignment, delivery excellence, and measurable business outcomes.
  • Establish enterprise portfolio and PMO standards, including governance frameworks, stage\-gate reviews, risk and dependency management, executive reporting, and intervention plans for critical initiatives.
  • Drive executive decision\-making through data\-driven portfolio insights, providing visibility into priorities, investments, milestones, risks, resource constraints, business impacts, and strategic tradeoffs.
  • Lead the Data \& AI organization's governance and operating rhythms, including portfolio reviews, operational reviews, financial performance discussions, KPI management, and executive decision forums.
  • Partner with Finance, Procurement, Legal, and business stakeholders to strengthen financial and commercial management through budgeting, forecasting, vendor governance, cost transparency, contract oversight, and value realization.
  • Champion organizational change, adoption, and benefits realization by leading stakeholder engagement, communications, training, business readiness, and post\-implementation value assessments.
  • Establish and govern service management practices across critical Data \& AI platforms, driving service reliability, observability, resilience, operational excellence, and continuous improvement.
  • Reduce cost\-to\-serve and improve operational performance through process simplification, automation, AI\-enabled operations, and proactive incident and problem management.
  • Serve as a trusted advisor to senior leadership on portfolio strategy, execution risks, organizational effectiveness, operational performance, and investment priorities.
  • Build and develop high\-performing teams across portfolio management, PMO, business operations, vendor management, and service excellence functions while fostering a culture of accountability, continuous improvement, and collaboration.

Must\-Have Qualifications

  • Bachelor's degree with 15\+ years of progressive experience in portfolio management, PMO leadership, business operations, program governance, enterprise transformation, or technology leadership, including 10\+ years of people leadership experience; or an advanced degree with 13\+ years of relevant experience and 10\+ years of people leadership experience.
  • Proven success leading large\-scale, enterprise\-wide portfolios comprised of complex, interdependent programs with significant executive visibility, strategic importance, and cross\-functional stakeholder engagement.
  • Demonstrated experience designing and implementing portfolio governance frameworks, operating models, prioritization processes, delivery standards, and execution disciplines within highly matrixed global organizations.

Nice\-to\-Have Qualifications

  • Experience leading enterprise Data, Analytics, Artificial Intelligence (AI), Digital, Platform, Technology, or business transformation portfolios.
  • Proven track record building, scaling, or leading Enterprise PMO, Portfolio Management, Business Operations, Strategy Execution, or Transformation Management functions.
  • Strong knowledge of enterprise technology operations, service management, platform delivery, Site Reliability Engineering (SRE), AIOps, operational excellence, or continuous improvement disciplines.
  • Demonstrated success improving operational performance, service reliability, automation, observability, and business outcomes through technology\-enabled transformation initiatives.
  • Experience managing large\-scale technology investments, strategic supplier relationships, outsourced services, and complex commercial agreements.
  • Executive presence with exceptional communication, change leadership, and influencing skills, including the ability to effectively engage and build credibility with senior leaders across business and technology functions.
  • Strong financial and operational acumen with experience managing portfolio investments, budgeting, forecasting, resource planning, vendor governance, and business case development to drive measurable business outcomes.

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

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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):$209,600\.00 \- $314,400\.00

This position is eligible for a short\-term incentive called the Medtronic Incentive Plan (MIP).

This position is eligible for an annual long\-term incentive plan.

The base salary range is applicable across the United States, excluding Puerto Rico and specific locations in California. The offered rate complies with federal and local regulations and may vary based on factors such as experience, certification/education, market conditions, and location. 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 $209K-$314K range is above the 75th percentile 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

Company Medtronic
Title Sr. Director, Data & AI Program Portfolio Management
Location Minneapolis, MN, US
Category AI/ML Engineer
Experience Senior
Salary $209K - $314K
Remote No

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 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 (52% of roles) Aws (28% of roles) Azure (22% of roles) Rag (21% of roles) Gcp (15% of roles) Pytorch (15% of roles) Prompt Engineering (14% of roles) Kubernetes (13% of roles)

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 ($262K) sits 22% above the category median. Disclosed range: $209K to $314K.

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.

Medtronic AI Hiring

Medtronic has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Mounds View, MN, US, Minneapolis, MN, US. Compensation range: $199K - $314K.

Location Context

Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 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

Based on 6,420 roles with disclosed compensation, the median salary for AI/ML Engineer positions is $214,900. Actual compensation varies by seniority, location, and company stage.
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.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Medtronic is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI/ML Engineer positions include ML Architect, AI Engineering Manager, Principal ML Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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