Interested in this AI/ML Engineer role at GE HealthCare?
Apply Now →Skills & Technologies
About This Role
Job Description Summary
===========================
The AI Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and collaborative development environment. In this role, you will contribute to the development and deployment of modern machine learning methods for finding structure in large healthcare data sets.
At GE HealthCare, we are committed to bringing AI and cloud\-based solutions for our customers: all aspects of computing services across the cloud and edge – including advanced analytics, visualization, multi\-modal learning, servers, databases, storage, networking, analytics, software, intelligence are delivered over the Internet. Our Science \& Technology organization is harnessing the power of technology to make healthcare more precise, more personalized, and more accessible for everyone. From driving the overall clinical research and patient\-centric innovation strategy to delivering new digital and machine learning capabilities \- we’re committed to leading digital transformation, improving outcomes for patients and providers, and creating a world where healthcare has no limits.Job Description
===================
Roles and Responsibilities
Are you passionate about using AI to transform healthcare? We are looking for a highly motivated individual, passionate about foundational AI models to join the GE Healthcare AI group. As the Senior Staff AI Scientist, you will focus on exciting generative AI problems, large\-scale pretraining, prompt tuning, distillation, robustness, responsible AI, quantization, etc.
Additionally, you will be responsible for:
- Developing and implementing novel machine learning algorithms particularly in the area of LLM to provide automation of clinical tasks using one or more of electronic medical records, waveforms, and clinical reports.
- Demonstrating algorithms to meet accuracy requirements on general subject population through statistical analyses and error estimation.
- Exploring learning from human feedback and assisting humans evaluating AI.
- Building prototypes to enable development of high\-performance AI algorithms in scalable, product\-ready code.
- Working with large\-scale datasets, designing, and developing generative algorithms.
- Staying current on published state\-of\-the\-art algorithms and competing technologies.
Basic Qualifications
- Master’s Degree in a “STEM” major (Science, Technology, Engineering, Mathematics) or equivalent field plus 6 years of relevant research OR Ph.D. in a “STEM” major (Science, Technology, Engineering, Mathematics) or equivalent field with 6 years of relevant research.
- Publications as first author on LLM, Agentic AI or self supervised learning (SSL).
- Demonstrated expertise in building large scale AI such as generative AI models.
- Implementation experience with a variety of high\-level languages (e.g. Python, C\+\+)
- Experience with high\-dimensional imaging data and waveform/time\-series data.
Preferred Qualifications
- Experience and demonstrated capability to handle challenges with vague or abstract problem definition.
- Experience with frameworks and tools such as DeepSpeed, HuggingFace, Megatron, PyTorch lightning, etc.
- Experience with various MLOps, ModelOps, FMOps (Foundation Model Ops) methods.
- Experience working with large scale AI training.
- An in\-depth understanding of machine learning algorithms and modeling (e.g., semi\-supervised or weakly supervised learning, generative models, transfer learning, optimization, large language models, etc.)
- Track record in developing machine learning solutions using massive real\-world data for solving real world business problems.
- In depth experience with Spark/Hadoop and either PyTorch/Tensorflow
- Experience creating production environment data analytics and applications
Eligibility Requirements
- Must be willing to travel to attend meetings, workshops, conferences \& etc.
- Must be willing to work out of an office located in Bellevue, WA.
About Team
GE Healthcare teams are based in the US (San Ramon, Bellevue), France, Israel (Tel Aviv), and India (Bangalore). This gives us several core overlap hours for shared meetings.
Work/Life Balance
Our team also puts a significant value on work\-life balance. Having a healthy balance between your personal and professional life is crucial to your happiness and success here. We don’t focus on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well\-balanced life—both in and outside of work.
Mentorship \& Career Growth
We maintain diverse engineering, and leadership perspectives and backgrounds across technology and beyond. Our employees are excited to share their experiences and mentor more junior engineers. Team members are highly encouraged to set up mentorship relationships with seasoned engineers, not only in our team, but also across the broader GE Healthcare population.
We will not sponsor individuals for employment visas, now or in the future, for this job opening. For U.S. based positions only, the pay range for this position is $188,640\.00\-$282,960\.00 Annual. It is not typical for an individual to be hired at or near the top of the pay range and compensation decisions are dependent on the facts and circumstances of each case. The specific compensation offered to a candidate may be influenced by a variety of factors including skills, qualifications, experience and location. In addition, this position may also be eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). GE HealthCare offers a competitive benefits package, including not but limited to medical, dental, vision, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, and tuition reimbursement.
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID\-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: Yes
We will not sponsor individuals for employment visas, now or in the future, for this job opening. For U.S. based positions only, the pay range for this position is $188,640\.00\-$282,960\.00 Annual. It is not typical for an individual to be hired at or near the top of the pay range and compensation decisions are dependent on the facts and circumstances of each case. The specific compensation offered to a candidate may be influenced by a variety of factors including skills, qualifications, experience and location. In addition, this position may also be eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). GE HealthCare offers a competitive benefits package, including not but limited to medical, dental, vision, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, and tuition reimbursement.
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID\-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: Yes
Salary Context
This $188K-$282K 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
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 GE HealthCare, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($235K) sits 10% above the category median. Disclosed range: $188K to $282K.
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.
GE HealthCare AI Hiring
GE HealthCare has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Bellevue, WA, US. Compensation range: $240K - $282K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.