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About This Role
The Company
Dexcom Corporation (NASDAQ DXCM) is a pioneer and global leader in continuous glucose monitoring (CGM). Dexcom began as a small company with a big dream: To forever change how diabetes is managed. To unlock information and insights that drive better health outcomes. Here we are 25 years later, having pioneered an industry. And we're just getting started. We are broadening our vision beyond diabetes to empower people to take control of health. That means personalized, actionable insights aimed at solving important health challenges. To continue what we've started: Improving human health.
We are driven by thousands of ambitious, passionate people worldwide who are willing to fight like warriors to earn the trust of our customers by listening, serving with integrity, thinking big, and being dependable. We've already changed millions of lives and we're ready to change millions more. Our future ambition is to become a leading consumer health technology company while continuing to develop solutions for serious health conditions. We'll get there by constantly reinventing unique biosensing-technology experiences. Though we've come a long way from our small company days, our dreams are bigger than ever. The opportunity to improve health on a global scale stands before us.
Meet the team:
Our R&D organization is building the next generation of AI-powered experiences for people managing their health. As a Senior AI/ML Engineer in AI/ML Engineering, with a focus on AI research, you help shape the foundations of future AI-powered capabilities — from problem framing and experimental design through prototyping, validation, and translation into product. You’ll combine strong software engineering with hands-on expertise in modern AI, including foundation models, generative AI, and predictive modeling, to turn emerging research into reliable, safe, and valuable product capabilities.
You’ll help innovate and build the foundations of future AI-powered capabilities, partnering with engineers, product managers, and clinical, regulatory, and commercial stakeholders to translate emerging technologies into real-world impact. In doing so, you’ll help position Dexcom as an industry leader in health AI and empower millions of customers to take control of their health.
Where you come in:
- You research, design, develop, prototype and validate novel AI/ML technologies, translating emerging scientific advances into high-impact opportunities for future product innovation while building reusable, high-quality research and prototype code.
- You investigate and advance state-of-the-art approaches in areas such as foundation models, multimodal learning, and time-series modeling, assessing their potential to address challenging customer, clinical, and business problems.
- You own evaluation and safety for your systems, defining metrics, benchmarks, and monitoring, identifying model and system risks, and driving mitigations and responsible-AI practices across the team.
- You lead technical strategy that balances model performance, latency, cost, safety, and regulatory requirements.
- You publish and present research at leading conferences and journals, clearly communicate complex methods and results to technical and non-technical audiences, and contribute to the broader AI community and Dexcom’s leadership in health AI.
- You coordinate with cross-functional teams — including stakeholders from R&D, Commercial, Product, Legal, and Regulatory — to ensure development aligns with company strategy and meets the highest safety standards.
You build and improve the research and training infrastructure, including data, experimentation, and CI/CD pipelines, applying reliability, observability, and cost-awareness to accelerate the team’s work. *
What makes you successful:
- You love being on the cutting edge of AI/ML, bring a strong research mindset that keeps you current with advances and eager to explore new ideas and methods, and share a passion for Dexcom’s mission and health-sensing applications.
- You have strong CS fundamentals and hands-on experience with Python and modern AI/ML libraries and frameworks, with depth in areas such as deep learning, generative AI, reinforcement learning, and multimodal learning.
- You have experience independently conducting rigorous AI/ML research, from problem formulation and experimental design through validation and communication of results.
- You have experience working with large-scale datasets and leveraging cloud-based and distributed computing environments to accelerate AI/ML research, model development, and experimentation.
- You combine strong software engineering practices with sound experimental methodology to produce reliable, reproducible, and scalable AI research.
- You bring a responsible-AI mindset — attentive to model safety, reliability, and risk in regulated, high-stakes settings.
You have a demonstrated record of contributing to the broader scientific community through conference publications, journal articles, patents, invited talks, or open-source contributions. *
What you’ll get:
- A front row seat to life changing CGM technology. Learn about our brave #dexcomwarriors community .
- A full and comprehensive benefits program.
- Growth opportunities on a global scale.
- Access to career development through in-house learning programs and/or qualified tuition reimbursement.
An exciting and innovative, industry-leading organization committed to our employees, customers, and the communities we serve. *
Travel Required:
5-15%
*
Experience and Education Requirements:
Typically requires a Bachelor’s degree in a technical discipline, and a minimum of 5-8 years related experience or Master’s degree and 2-5 years equivalent industry experience or a PhD and 0-2 years experience.
Remote Workplace: Your location will be a home office; you are not required to live within commuting distance of your assigned Dexcom site (typically 75 miles/120km). If you reside within commuting distance of a Dexcom site (typically 75 miles/120km) a hybrid working environment may be available. Ask about our Flex workplace option.
Please note: The information contained herein is not intended to be an all-inclusive list of the duties and responsibilities of the job, nor are they intended to be an all-inclusive list of the skills and abilities required to do the job. Management may, at its discretion, assign or reassign duties and responsibilities to this job at any time. The duties and responsibilities in this job description may be subject to change at any time due to reasonable accommodation or other reasons. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability. Dexcom’s AAP may be viewed upon request by contacting Talent Acquisition at [email protected].
If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact Dexcom Talent Acquisition at [email protected].
Meritain, an Aetna Company, creates and publishes the Machine-Readable Files on behalf of Dexcom. To link to the Machine-Readable Files, please click on the URL provided: https://health1.meritain.com/app/public/#/one/insurerCode=MERITAIN_I&brandCode=MERITAINOVER/machine-readable-transparency-in-coverage?reportingEntityType=TPA_19874&lock=true
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Dexcom. Only authorized staffing and recruiting agencies may use this site or to submit profiles, applications or resumes on specific requisitions. Dexcom does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to the Talent Acquisition team, Dexcom employees or any other company location. Dexcom is not responsible for any fees related to unsolicited resumes/applications.
AI in Hiring Notice: We may use AI supported tools to help make our hiring process more efficient, consistent, and accessible for candidates around the world. All hiring decisions are made by people.
Salary:
$135,100.00 - $225,100.00
#DexcomUS
Salary Context
This $135K-$225K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Dexcom, 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 $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($180K) sits 15% below the category median. Disclosed range: $135K to $225K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Dexcom AI Hiring
Dexcom has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $225K - $273K.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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