ML / AI Jobs in United States
There are 4,262 open ML / AI jobs in United States on freehire right now. 783 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 | $190,600 | $223,000 | $256,500 | 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 37%
- deep-learning 27%
- tensorflow 26%
How the work is done
- Remote 693 · 16%
- Hybrid 531 · 12%
- Onsite 383 · 9%
Visa sponsorship offered in 63% of the 1,015 postings that state a position on it.
Seniority
- Senior 1,214
- Staff 466
- Lead 218
- Principal 205
- Intern 104
- C-level 58
Who is hiring
- 1000+ employees 1,182
- 501-1000 employees 278
- 11-50 employees 127
- 51-200 employees 101
- 201-500 employees 26
- 1-10 employees 5
AI/ML Engineer - Automation/Robotics
Build and maintain AI/ML systems for robotics, including training evaluation pipelines, model fine-tuning, deploying algorithms in simulation and on physical hardware, and integrating robotic control and perception stacks.
ML Engineer - Instawork Robotics
Build and scale data labeling and enrichment pipelines for robotics/AI training data, using AWS distributed systems, data pipelines, and ML/CV model development.
Senior, Machine Learning Engineer - 3D Perception
Senior Machine Learning Engineer designing and deploying 3D perception models for autonomous trucks, using PyTorch and multi-modal sensor data to improve environmental understanding.
Machine Learning Engineer, II - 3D Perception
Build and improve 3D perception models (LiDAR, cameras) for autonomous trucks using PyTorch and Python, integrating ML into Torc’s autonomy stack.
Ai/ml Engineer
Build and optimize AI/ML models for computer vision tasks using TensorFlow/PyTorch, deploying scalable solutions on AWS with CI/CD pipelines.
Sr. Ai/ml Engineer
Builds and deploys AI/ML models and LLM applications, focusing on prompt optimization, sandbox experimentation, and cloud-based pipelines for a core-AI product company.
Ai/ml Engineer
Build and deploy AI/ML models (LLMs, RAG, NLP, generative AI) on a large-scale platform using Python, TensorFlow, Scikit-learn, and AWS, with full MLOps and data engineering responsibilities.
Machine Learning Engineer
Design and deploy ML systems (CNN, RNN, LSTM), optimize MLOps pipelines, and run distributed training using Spark and Kubernetes in a fully remote, short-term contract role.
Machine Learning Engineer
Design and deploy advanced ML models (CNNs, RNNs, LSTMs) using Kubernetes and MLOps pipelines; optimize models for scale with distributed training and Apache Spark.
Deep Learning Engineer
Design, optimize, and deploy deep learning models using Python, PyTorch, and TensorFlow on AWS/GCP in a fully remote, hourly contract role.
Machine Learning Engineers
Machine Learning Engineer designing, developing, and implementing ML models and optimizing pipelines in a fully remote role using Python, Java, cloud ML services, and frameworks like TensorFlow/PyTorch.
Applied AI ML Engineer Lead
Lead applied AI/ML engineer architecting and delivering autonomous agent systems and generative AI solutions for JPMorgan Chase's Commercial and Investment Banking division, bridging research and enterprise-grade production deployment.
Senior Software Engineer, Global Banking & Markets, AI/ML Technology
Build low-latency, cloud-native trading systems in Java and integrate AI coding agents to accelerate development and modernize legacy codebases for Goldman Sachs' Global Banking & Markets division.
Software Engineer III - AI/ML Developer
Builds and maintains AI/ML systems and infrastructure for a large bank, using Python, ML frameworks, and cloud platforms while integrating enterprise-approved AI-assisted development tools.
Amazon TPM, AI/ML Infrastructure Planning, AI/ML Infrastructure Planning
Technical Program Manager driving AI/ML-powered planning automation and process improvement across AWS global infrastructure planning, working cross-functionally with operations, finance, and engineering teams.