Interested in this AI/ML Engineer role at Baxter?
Apply Now →Skills & Technologies
About This Role
Req \# JR \- 198491
Location Marion, North Carolina, United States
Job Category Maintenance
Date posted 03/31/2026
Apply Now
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
This is where we make life\-saving products
You have deep knowledge of and experience with manufacturing processes. You understand the importance of building relationships, establishing order, and maintaining clear communication channels. As a Maintenance Planner, you are willing to listen and inspire others by your actions. You also appreciate the stability of a large multinational company with a long history of growth and success. Your team is an extension of your family, and you know how to support them as individuals while helping them achieve results as a team.
Your Team
Baxter is focused on saving and sustaining lives by finding solutions to complex problems. Each day, the manufacturing team strives to create quality products for our customers—and are sometimes met with unforeseen issues to solve. The high\-caliber talent at Baxter meets these challenges head\-on, as a team, to create products with the customer's needs top\-of\-mind.
We build relationships with each other to get work done.
As a multidisciplinary environment, we are always learning from others and exchanging ideas. This means we are open to new opinions and encourage Baxter employees always to be their authentic selves and celebrate our various backgrounds.
A manufacturing facility is a high\-energy environment with little downtime. We have robust processes that ensure our employees are safe and healthy—both mentally and physically. We pride ourselves on being top of the line regarding cleanliness and safety.
What we offer from Day One:
- Shift flexibility to trade shifts and leverage overtime opportunities
- Medical, Dental and Vision coverage
- 160 hours of Paid Time Off and Paid Holidays
- 401K match
- Employee Stock Purchase Program
- Paid Parental Leave
- Tuition Reimbursement
We provide opportunities for you to continue to learn through training, conferences, certifications, and support for advanced degrees. Growth from role to role or level to level is encouraged and is supported by management to ensure employees are consistently engaged with their work.
What you'll be doing
- Assess service requests for validity, accuracy, clarity and completeness. Ensure compliance and expectations prior to approving service request.
- Manage work order and service request backlog.
- Prioritize and plan work orders based on asset criticality.
- Plan all aspects of non\-emergency work orders to include parts required, estimated labor hours, special tools, detailed instructions and any coordination with contractors, other departments and support groups.
- Partner with maintenance, operations, quality, stockroom and vendors as necessary to ensure backlog work orders include everything necessary to complete the work order.
- Partners with other plant personnel to plan and schedule maintenance work.
- Work with technicians and reliability engineers to create non\-Preventive Maintenance (PM) / non\-Predictive Maintenance (PdM) job plans to include parts required, technical specifications, special tools and detailed instructions.
- Manage the maintenance job plan library.
- Use parts kitting process for PMs and all other work orders that can be scheduled and kitted.
- Discuss job details with originator of the work order as needed to clarify work and plan as required.
- Work closely with maintenance supervisors to ensure weekly assignments are delivered on time to continue supporting the planning process.
- Update job plans based on feedback from technicians, supervisors, managers and department engineers.
- Raise issues for requested work which does not appear to be valid, feasible or has cost constraints, or requires engineering design/change control.
- Prepare and submit ‘addition\-to\-stores’ requests as required.
What you'll bring
- Must be at least 18 years of age, High School Diploma or GED required, A.A.S in related curriculum preferred.
- Required to acquire planner certification within 1 year of employment.
- Minimum 5 years of previous industrial maintenance experience required.
- Minimum 2 years of previous industrial maintenance experience in assigned area preferred.
- Must have the knowledge, skill and ability to perform corrective, preventive, predictive and improvement tasks and projects on industrial assets and systems to develop job plans for others to implement.
- Knowledge and proficiency with Microsoft Office computer software and Maximo CMMS.
- Understand verbal and written safety and quality instructions and read and comprehend written work instructions including words and drawings.
- Must have basic English written and oral communication skills adequate to communicate with other team members.
Other Duties as Assigned
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. Overtime is worked as required.
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 $46,400\- $63,800 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.
\#LI\-EB1
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 $46K-$63K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($55K) sits 67% below the category median. Disclosed range: $46K to $63K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Baxter AI Hiring
Baxter has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Batesville, IN, US, Marion, NC, US, Round Lake, IL, US. Compensation range: $63K - $90K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.