Interested in this AI/ML Engineer role at Commure?
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About This Role
At Commure, we're building the AI Operating System for healthcare, the foundation that defines how care is delivered, documented, and financed. Our platform spans the full care journey: Ambient AI and Dictation eliminating documentation burden at the point of care, intelligent Agents automating patient and revenue workflows, and autonomous RCM processing billions in claims, all on a single AI\-native platform integrated with 60\+ EHRs.
Healthcare carries a $1 trillion administrative burden and we're at the center of transforming it. Today, 500,000\+ clinicians across 500\+ healthcare organizations nationwide trust Commure to handle $25B\+ in annual claims and support over 200 million patient interactions. Our latest $70M raise at a $7B valuation reflects the confidence the market has placed in this mission. We've also been named to the Fortune Future 50 list and the 2026 AI Breakthrough Awards for “Overall NLP Company of the Year.”
Our team works directly alongside clinicians, not through layers of process, which means the gap between what you build and its impact on patient care is immediate. We move fast, deploy daily, and take full ownership from early thinking to production. If you're energized by hard problems, high stakes, and a team that holds itself to a high bar, you'll find your people here.
The future of healthcare is being built right now. Come deliver this transformation.
About the Role
At Commure, our Ambient AI team is at the forefront of revolutionizing healthcare technology by building AI solutions that span the entire care journey, from the patient visit to the final claim. You'll work across real\-time clinical documentation powered by LLMs, AI\-driven billing automation that improves revenue capture and reduces denials, and a clinical intelligence platform that grounds answers in live patient context. If you love working on important, exciting problems in healthcare and love shipping quickly, come join us!
What You’ll Do
- Build end\-to\-end products to revolutionize Ambient AI for providers and administrators
- Be a part of a tremendously fast\-paced team that celebrates fast execution and decisions
- Work across the entire software stack
- Work with a stack that includes Python, Javascript, React, Flutter, Flask, and other frameworks
- Work directly with customers to solve their issues daily
What You Have
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent extensive experience
- Professional software development industry experience
- Strong Full\-Stack programming skills
- Very familiar with Frontend technologies (React, Flutter, Typescript, etc.)
- Experience in environments where you have to ship quickly. We move fast.
- General Understanding of Containers and Cloud (Docker, Kubernetes)
- Excitement to work in a high impact field with a builder attitude!
- Experience building production environments
+ Alerting and reporting
+ Metrics tracking
+ Software reliability engineering
+ Great product sense
- Attention to detail around user experience and customer needs
- Extremely motivated to grow
- Strong leadership skills
Please be aware that all official communication from us will come exclusively from email addresses ending in @commure.com. Any emails from other domains are not affiliated with our organization.
Employees will act in accordance with the organization’s information security policies, to include but not limited to protecting assets from unauthorized access, disclosure, modification, destruction or interference nor execute particular security processes or activities. Employees will report to the information security office any confirmed or potential events or other risks to the organization. Employees will be required to attest to these requirements upon hire and on an annual basis.
Compensation Range: $130K \- $180K
Salary Context
This $130K-$180K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Commure, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($155K) sits 29% below the category median. Disclosed range: $130K to $180K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Commure AI Hiring
Commure has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span New York, NY, US, Mountain View, CA, US. Compensation range: $180K - $240K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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