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About This Role
This is where your work makes a difference.
At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond.
Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results.
Here, you will find more than just a job—you will find purpose and pride.
Your role at Baxter
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This role provides senior leadership for developing and advancing global environmental sustainability climate risks strategy, including strategic leadership for governing programs, management system elements, sustainability goals, and other related programmatic activities in alignment with company
Sustainability ‘Protect the Planet’ commitments in conjunction with Sustainability Office and Integrated Supply Chain risk and resiliency efforts.
This position is also responsible for overseeing key sustainability mandatory & voluntary reporting elements in coordination with the EHS&S site and corporate teams, CSO, ESG Controller and legal; and effective management of internal and external resources in support of those activities.
The individual in this role will cultivate relationships inside Baxter among various cross functional working groups and teams, including ISC, Enterprise Risk Management, Finance, Communications, Legal, Engineering, EHS&S; as well as outside Baxter in order to further advance the company’s sustainability climate goals, including routine engagements with external professional/industry groups, customers and other key stakeholders.
What you'll be doing
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- Builds and develop environmental sustainability reportingprocess and structure improvements to drive execution, efficiency, accuracy and completeness of externally facing data.
- Monitors reporting body initiatives and regulatory requirements to ensure alignment with reporting processes and controls; including partnering with CSO and ESG to complete the following frameworks: Corporate Sustainability Reporting Directives (CSRD), International Sustainability Standards Board (ISSB),Taskforce Climate Financial Disclosure(TCFD), CDP.
- Evaluates and provides direction on selecting appropriate frameworks and reporting structures for Baxter.
- Leads compliance initiatives for the company, including identifying environmental data gaps and collaborating with functional leads to implement improvements.
- Advises on software platform selection/modifications and supports the implementation of effective data solutions.
- Represents EHS&S/ Operational Environmental Sustainability team as CR Report Core Team Member; coordinates with team members for data review/prep in support of Protect the Planet commitments. Primary point of contact assuring all internal content, including main report narrative, performance data, appendices, Supplemental Content, Climate Action Roadmap are accurate and representative of Baxter sustainability performance.
- Conducts outreach with peers for benchmarking; engages with external stakeholders, and industry groups to assess performance and provide recommendations for strategic value drivers.
- Develops controls process for data, including KPIs, dashboards and data roll-up. Evaluates integration of data reportinginto Baxter’s management systems and ensures both internal (monthly) and external (annual) reporting processes are in place and driven effectively.
- Creates and leads monthly performance reporting process.
- Oversees segment sustainability reporting and assurance processes to minimize Baxter’s reputational risk and meet internal and external partner expectations.
- Development of the company wide decarbonization strategy, including risk mitigation and Renewable Electricity transition to 100% cost-effective sourcing in alignment with GHG Protocol carbon accounting standards.
- Leads the Climate Resiliency Pillar in partnership with the Risk & Resiliency (ISC), Risk Management, and Sustainability organizations. Ensuring long-term success and compliance with evolving environmental and sustainability governance requirements.
- Manages the Climate Resiliency program in alignment with the corporate risk management reporting framework, ensuring proactive identification and mitigation of climate-related risks.
- Monitors potential sustainability-related tax implications, identifies and provides recommendations for subsidy opportunities that support Baxter’s environmental initiatives.
- Provides input into the development of Baxter’s global sustainability roadmaps, ensuring alignment with strategic priorities and environmental impact goals.
- Influences cross-functionally to drive Operational Environmental Strategy, including EHSS, Corporate Responsibility, ESG Controller, Procurement, Human Resources, Legal, etc., to foster a culture of sustainability by integrating environmental priorities into core business functions and decision-making processes.
- Provides thought leadership and garners consensus from cross-functional leaders and company leadership on corporate Environmental Sustainability Reporting, and Climate Risks, supporting initiatives, investment areas and overall execution plan.
- Partners with leadership to develop ISC Supply Chain strategy and environmental sustainability goals, including communication, engagement and implementation planning.
- Development of company-wide strategy for goals and initiatives as part of the CR/ESG Strategy and in alignment with the Sr. Director and the Leadership Team.
- Coaches, advises, and builds proficiency of Baxter cross-functional leaders, and working group leads on ways to improve outcomes and position the company for regulatory compliance on environmental, social, and governance topics.
- Applies data analytics & innovation to analyze ongoing initiatives as well as the environmental impact of operations, track progress, and make informed decisions to optimize sustainability efforts.
- Partners with Internal Audit and Finance/ESG Controller to ensure environmental sustainability data is assured to standard & in accordance with existing and emerging requirements.
- Drives critical communications around the business impacts of environmental sustainability reporting requirements/ commitments and progress against goals to leadership; uses influence to advance CR/ESG strategy overall for Baxter.
What you'll bring
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- Bachelor's degree in environmental science, engineering subject area or equivalent degree
- Preferred, a Master’s in Corporate Environmental Management, or Sustainable Business or equivalent or 10+ years of Environmental Corporate Reporting.
- 12+ years of professional-level experience leading environmental governance, developing sustainability programs, leading partners and embedding sustainability into global businesses.
- Extensive experience interpreting and applying state and federal environmental sustainability regulations, as well as other global environmental regulatory regimes.
- Excellent project management, program management, communication, and interpretation of complex environmental data and trends.
- Showed success leading and actively engaging large teams with a clear vision and positive outcomes in a collaborative environment with a bias for action.
- Strong networking skills.
- Must be able to communicate complex technical issues clearly to a variety of audiences, from senior leaders to plant personnel.
- Work well in a collaborative, matrix environment.
- Proven track record of interpersonal and leadership skills with ability to interface well with other departments.
- Ability to manage multiple priorities.
- Ability to respond to detailed inquiries and present information to groups and senior leaders.
- Strong business acuity.
- Green or Black Belt certification preferred.
- Professional certifications preferred.
We understand compensation is an important factor as you consider the next step in your career. At Baxter, we are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. The estimated base salary for this position is $144,000 - $198,000 annually. The estimated range is meant to reflect an anticipated salary range for the position. We may pay more or less than of the anticipated range based upon market data and other factors, all of which are subject to change. Individual pay is based on upon location, skills and expertise, experience, and other relevant factors. This position may also be eligible for discretionary bonuses. For questions about this, our pay philosophy, and available benefits, please speak to the recruiter if you decide to apply and are selected for an interview.
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.
US Benefits at Baxter (except for Puerto Rico)
This is where your well-being matters. Baxter offers comprehensive compensation and benefits packages for eligible roles. Our health and well-being benefits include medical and dental coverage that start on day one, as well as insurance coverage for basic life, accident, short-term and long-term disability, and business travel accident insurance. Financial and retirement benefits include the Employee Stock Purchase Plan (ESPP), with the ability to purchase company stock at a discount, and the 401(k) Retirement Savings Plan (RSP), with options for employee contributions and company matching. We also offer Flexible Spending Accounts, educational assistance programs, and time-off benefits such as paid holidays, paid time off ranging from 20 to 35 days based on length of service, family and medical leaves of absence, and paid parental leave. Additional benefits include commuting benefits, the Employee Discount Program, the Employee Assistance Program (EAP), and childcare benefits. Join us and enjoy the competitive compensation and benefits we offer to our employees. For additional information regarding Baxter US Benefits, please speak with your recruiter or visit our Benefits site: Benefits | Baxter
Equal Employment Opportunity
Baxter is an equal opportunity employer. Baxter evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.
Know Your Rights: Workplace Discrimination is Illegal
Reasonable Accommodations
Baxter is committed to working with and providing reasonable accommodations to individuals with disabilities globally. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application or interview process, please click on the link here and let us know the nature of your request along with your contact information.
Recruitment Fraud Notice
Baxter has discovered incidents of employment scams, where fraudulent parties pose as Baxter employees, recruiters, or other agents, and engage with online job seekers in an attempt to steal personal and/or financial information. To learn how you can protect yourself, review our Recruitment Fraud Notice.
Salary Context
This $144K-$198K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Baxter, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($171K) sits 11% above the category median. Disclosed range: $144K to $198K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Baxter AI Hiring
Baxter has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in MI, US. Compensation range: $198K - $198K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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