Salary guide
| Measure | Annual pay (USD) |
|---|---|
| 25th percentile | $206,000 |
| Median | $242,000 |
| 75th percentile | $278,000 |
| Lowest listing | $100,000 |
| Highest listing | $560,000 |
| Listings counted | 307 |
| Level | Listings | Median pay |
|---|---|---|
| Mid-level | 19 | $260,000 |
| Senior | 101 | $232,000 |
| Country | Currency | Listings | Median pay | Middle half |
|---|---|---|---|---|
| United States | USD | 283 | $244,000 | $207,000 to $280,000 |
| Canada | USD | 12 | $232,000 | $182,000 to $255,000 |
Our Monetization team works on challenging problems every day.
As a Staff Machine Learning Engineer for the Coupang Media Group (CMG) - Ads Quality & Ranking , you will be responsible for designing and deploying state-of-the-art machine learning models, ranking algorithms, and optimization systems powering our advertising platform.
As our Staff Machine Learning Engineer for Coupang Media Group (CMG), Offsite Ads , you will be responsible for defining and building the next generation of machine learning systems, optimization platforms, and AI-native advertising products that power Coupang's rapidly growing…
You will join as a technical leader shaping both the product architecture and team culture. This is a rare opportunity to define the industry standard for AI security at Cisco’s global enterprise scale.
Labelbox · 3mo ago
We build the data, environments, and evaluations that frontier labs use to train and judge their agents. This role sits where training meets infrastructure.
Jobgether · 7d ago
Our partner is looking for a Staff Machine Learning Engineer - Team Lead (Active Secret Clearance) based in the United States. Join a mission-driven engineering team developing advanced AI systems for complex, real-world government applications.
Pacific Northwest National LaboratoryNew · 2d ago
At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.
Design, build, and scale the recommendation systems that connect new users to communities and content, from candidate generation and ranking through to online serving.
The ML Infrastructure team builds and operates the inference stack that serves SambaNova's models on RDU accelerators, from request scheduling and caching through the public APIs in SambaStack and SambaCloud.
Join an AI-focused team building the systems layer for a process intelligence platform. You will turn complex enterprise data into reliable, useful product experiences powered by hosted AI models.
Join Scale's ML platform team to develop RLXF, the internal distributed framework powering ML engineers, researchers, and data scientists. Work on cutting-edge large language model systems for fast and automated operations.
Scale AI · 9mo ago
As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems.
We’re part of Plaid’s Data organization, building models that help millions of people better understand and grow their financial lives.
Lead the design and development of large-scale RL training frameworks to accelerate the development of multi-modal AV foundation models. Design, build, and optimize simulation and data processing pipelines to enable scalable training of driving policies.
Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases.
We are looking for a Senior Machine Learning Engineer, Voice Experience to help build the next generation of AI-powered voice systems for the contact center.
Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.
The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation.
Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest.
Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest.
Lucid Motors · 1y ago
The GeoAI team is building next-generation AI-powered data automation platforms for ADAS and autonomous driving.
At ZipRecruiter, we sit on a massive universe of data—over a billion archived job postings, tens of millions of dynamic job seekers, and billions of impressions, clicks, and application events.
You will architect and maintain Airbnb’s end-to-end traffic classification ML systems, balancing high-performance model deployment with rigorous offline data pipelines.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Waymo · 2mo ago
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Waymo · 6mo ago
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
Nebius · 3mo ago
As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment.
This role owns the infrastructure that makes large-scale training and RL experiments possible, reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering.
SnapNew · 2d ago
Design and develop machine learning systems across the third-party signal lifecycle, from acquisition and curation to matching, attribution, and causal measurement. Design, implement, and scale critical machine learning models to support Snap's monetization strategies.
Design, implement, and scale critical machine learning models and systems to protect Snapchatters around global from harmful content and bad actors, promote a healthy content ecosystem through effective moderation, and ensure regulatory compliance.
We’re hiring a Senior Machine Learning Engineer to join our AI team, reporting directly to the Head of AI. Signals tell you what happened. Our job is to explain why — and that is the problem you will work on.
This is a hands-on MLOps engineering role. You will work across model training and refresh workflows, APIs, orchestration, data pipelines, production monitoring, and user-facing experiences such as model dashboards and training controls.
Join the Ads team as a Machine Learning Engineer and become a key contributor to Reddit’s business. In this hands-on role, you will be responsible for the full lifecycle of our ML systems, from initial research and modeling to deployment and optimization in production.
Airbnb · 4mo ago
The Assistance Engineering Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience.
When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes.
In this role, you will architect, build, and scale enterprise-grade AI/ML and Generative AI solutions—including predictive models, RAG architectures, and autonomous agentic workflows—that power Cisco IQ and our next-generation Customer Experience platform.
Architect and build production Agentic AI systems for compliance automation, including LLM-powered agents, orchestration pipelines, and decision support workflows that replace manual compliance processes.
The median Machine Learning Engineer salary in our $100k+ listings is $242,000 a year, based on 307 live USD listings. The middle half of listings pays $206,000 to $278,000. These figures cover only listings that publish a salary of $100k+ or more, so they sit above pay for Machine Learning Engineer roles overall.
Individual $100k+ Machine Learning Engineer listings range from $100,000 to $560,000 a year. The 25th percentile of listing midpoints is $206,000 and the 75th percentile is $278,000.
Median pay by level in our $100k+ listings: mid-level $260,000 (19 listings), senior $232,000 (101 listings). Levels with fewer than 5 listings are left out.
The companies with the most open $100k+ Machine Learning Engineer listings are Waymo (39 listings, median $238,000), Reddit (19 listings, median $276,000), Capital One (19 listings, median $206,000), Zoox (13 listings, median $295,000) and NVIDIA (13 listings, median $204,000).
The figures come from the salary ranges employers publish in their own job listings, collected from company career pages and applicant-tracking systems. Each listing counts once, at the midpoint of its range. Only USD listings go into the headline figures, and listings that are closed or stale are removed. The data was last refreshed on November 12, 2026.
Yes. Each listing is tagged remote, hybrid or on-site, and remote roles carry a region (US only, EMEA, APAC or global), so you can filter the live job list to the arrangement you want.
United States
Canada
