ML / AI Jobs in United States
There are 4,244 open ML / AI jobs in United States on freehire right now. 790 of them were posted recently. The skills employers ask for most often are machine-learning, ai and python.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| USD | year | $191,600 | $223,000 | $258,000 | 1,033 |
| USD | hour | $30 | $40 | $60 | 36 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- machine-learning 90%
- ai 77%
- python 61%
- pytorch 40%
- cloud 38%
- llm 36%
- deep-learning 27%
- tensorflow 26%
How the work is done
- Remote 681 · 16%
- Hybrid 528 · 12%
- Onsite 380 · 9%
Visa sponsorship offered in 63% of the 1,012 postings that state a position on it.
Seniority
- Senior 1,213
- Staff 466
- Lead 218
- Principal 203
- Intern 103
- C-level 57
Who is hiring
- 1000+ employees 1,180
- 501-1000 employees 278
- 11-50 employees 127
- 51-200 employees 100
- 201-500 employees 25
- 1-10 employees 5
Principal Machine Learning Engineer, Ads & Promos Delivery
Lead AI-driven ranking and relevance systems for DoorDash’s ads marketplace, designing and deploying ML/LLM models to personalize ad delivery in real time across global markets.
Senior Staff Machine Learning Engineer
Leads AI-driven ads and promotions delivery systems at DoorDash, designing real-time ranking/relevance models using deep learning, LLMs, and sequence modeling to optimize merchant-consumer matching across search/discovery platforms.
Staff Machine Learning Engineer - DashPass
Build and deploy large-scale ML systems to personalize offers and incentives for DoorDash’s DashPass loyalty program, optimizing subscriber acquisition, retention, and churn reduction.
Staff Machine Learning Engineer, Fulfillment Planning
Build and deploy large-scale ML systems that power real-time logistics decisions like delivery assignment and ETA estimation, shaping DoorDash’s fulfillment efficiency and cost.
Staff Software Engineer, Machine Learning - Personalization
Builds and deploys ML models for personalization and growth, focusing on recommendation systems and causal inference to enhance DoorDash’s grocery/retail search experience using PyTorch/TensorFlow in Python.
Software Engineer, Machine Learning Infrastructure - Generative AI
Builds and maintains the shared infrastructure that lets DoorDash teams safely deploy generative AI products, focusing on evaluation, observability, and agent systems using Python, distributed systems, and ML tooling.
Senior Software Engineer, Machine Learning Infrastructure - Generative AI
Build and scale the shared infrastructure that powers DoorDash’s generative AI products, including real-time and batch LLM inference, fine-tuning, and agent platforms across San Francisco, Sunnyvale, and Seattle.
Machine Learning Engineer, Drive
Build and deploy ML models for delivery ETAs, prep-time prediction, and logistics optimization at DoorDash Drive, using deep learning, reinforcement learning, and multimodal AI.
Staff Machine Learning Engineer, Causal Inference
A Staff Machine Learning Engineer focuses on causal inference at DoorDash, building production systems for uplift models, counterfactual evaluation, and connecting experiments with ML to drive decisions across new verticals like grocery and retail.
Principal Product Manager - AI/ML
Owns the AI/ML roadmap for Air’s Enterprise Readiness platform, defining features that automate decisions and integrate models into workflows for government and industrial users.
Director of Engineering, AI/ML
Lead a team to build and deploy AI/ML models that automate insurance operations and personalize customer/agent experiences, using deep learning, NLP, LLMs, and GenAI.
Senior ML/AI Engineer
Senior ML/AI Engineer designing and deploying production ML models for demand forecasting, sentiment analysis, and agentic AI systems at an early-stage AI-native consumer intelligence platform serving enterprise retail clients.
Machine Learning Engineer
Develop and deploy AI/ML models for national security applications, analyzing large datasets to extract insights and building scalable backend services and user interfaces.
Machine Learning Scientist, Algorithmic Recommendations (Email Targeting)
Designs and deploys machine learning models to optimize email targeting and content recommendations for The New York Times, using Python, SQL, and experimentation frameworks.
Lead Machine Learning Scientist, New AI Products and Platforms
Lead a team building embedding and language models to power AI-driven reader experiences at The New York Times, integrating LLMs into products while upholding journalistic independence.