Interested in this AI/ML Engineer role at Edwards Lifesciences?
Apply Now →About This Role
Innovation starts from the heart. Our Advanced Innovation \& Technology (AI\&T) teams harness the imagination, courage, and resourcefulness to think beyond what’s currently possible, and create solutions for patients many years into the future. If you’re an early\-stage innovator, then Edwards AI\&T team is the place for you to take the next steps in your career. We’ll give you the tools and resources you need to create groundbreaking innovations that shape the future of structural heart technology.
Imagine how your ideas and expertise can change a patient’s life. Our Global Operations \& Quality team plays a central part in ensuring our products are delivered to patients with cardiovascular disease. You’ll partner cross\-functionally with manufacturing operations and sales teams, delivering thoughtful solutions to complex challenges all while developing your knowledge of the medical device industry. Whether your work includes strategic inventory planning, labeling, warehouse management, material handling, or any of our other supply chain opportunities, you will be making a meaningful contribution to our team and to patients all over the world.
How you will make an impact:
- Drive optimization and redesign of manufacturing processes by applying advanced engineering methodologies (e.g., Six Sigma, Lean) to improve efficiency, quality, and scalability; ensure equipment, tooling, and fixtures meet performance and compliance standards
- Lead complex process development, qualification, and validation activities by designing and executing experiments and protocols; analyze data, generate insights, and deliver recommendations and technical reports
- Resolve complex manufacturing and compliance issues including CAPAs, non\-conformances, and audit observations, ensuring timely root cause identification and sustainable corrective actions
- Own and execute project plans for NPD initiatives by defining deliverables, managing risks, and ensuring alignment to customer expectations using structured project management tools and methodologies
- Provide technical leadership on the production floor by overseeing manufacturing support activities, guiding and developing technicians, and ensuring effective execution of testing and process controls
- Enable knowledge transfer and process adoption by developing clear, standardized documentation (e.g., work instructions, training materials) to support production readiness and operational consistency
- Perform other incidental duties as assigned by leadership
What you’ll need (Required):
- Bachelor's Degree in Engineering or Scientific field with 4 years experience including either industry or industry/education Or
- Master's Degree or equivalent in Engineering or Scientific field with 3 years experience including either industry or industry/education
- Ph.D. or equivalent in Engineering or Scientific field with industry experience or industry/education
What else we look for (Preferred):
- Experience with Edwards systems and training, including Windchill (PLM), strongly preferred, with demonstrated ability to navigate and leverage these tools to support product development and documentation processes
- Working knowledge of CAD and engineering design tools (as applicable), along with proficiency in MS Office Suite (including MS Project) to support technical analysis, planning, and execution
- Strong understanding of engineering principles, manufacturing processes, and equipment relevant to assigned areas, with the ability to apply this knowledge to solve complex problems
- Knowledge of applicable FDA regulations within the medical device industry, ensuring alignment with compliance, quality, and audit expectations
- Experience working with lab and/or industrial equipment (as applicable) to support testing, validation, and manufacturing activities
- Foundational understanding of statistical techniques to support data\-driven decision making and process validation
- Demonstrated problem\-solving, analytical, and critical thinking skills, with the ability to diagnose issues and recommend effective solutions
- Strong documentation and communication skills (written and verbal), with the ability to clearly convey technical information and engage effectively across stakeholders
- Proven leadership and influencing skills, with the ability to drive change and collaborate across cross\-functional teams
- Strong organizational skills and ability to manage competing priorities in a fast\-paced NPD and manufacturing environment
- Demonstrated attention to detail to ensure accuracy, quality, and compliance in all outputs
- Ability to build effective working relationships and interact professionally across all levels of the organization, including serving as a key contact on cross\-functional projects
- Ability to work effectively in team environments, including interdepartmental collaboration and project\-based work
- Adhere to all company rules and requirements (e.g., pandemic protocols, Environmental Health \& Safety rules) and take adequate control measures in preventing injuries to themselves and others as well as to the protection of environment and prevention of pollution under their span of influence/control
Aligning our overall business objectives with performance, we offer competitive salaries, performance\-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.
For California, the base pay range for this position is $108,000 \- $153,000 (highly experienced).
The pay for the successful candidate will depend on various factors (e.g., qualifications, education, prior experience). Applications will be accepted while this position is posted on our Careers website.
E dwards is an Equal Opportunity/Affirmative Action employer including protected Veterans and individuals with disabilities.
COVID Vaccination Requirement
Edwards is committed to protecting our vulnerable patients and the healthcare providers who are treating them. As such, all patient\-facing and in\-hospital positions require COVID\-19 vaccination. If hired into a covered role, as a condition of employment, you will be required to submit proof that you have been vaccinated for COVID\-19, unless you request and are granted a medical or religious accommodation for exemption from the vaccination requirement. This vaccination requirement does not apply in locations where it is prohibited by law to impose vaccination.
Salary Context
This $108K-$153K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Edwards Lifesciences, 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($130K) sits 28% below the category median. Disclosed range: $108K to $153K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Edwards Lifesciences AI Hiring
Edwards Lifesciences has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Irvine, CA, US, Alton, IL, US. Compensation range: $153K - $171K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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