ML / AI Jobs in United States
There are 4,332 open ML / AI jobs in United States on freehire right now. 793 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 | $191,800 | $223,200 | $258,000 | 1,021 |
| USD | hour | $30 | $39 | $60 | 37 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- machine-learning 90%
- ai 78%
- python 61%
- pytorch 40%
- llm 39%
- cloud 38%
- deep-learning 27%
- tensorflow 26%
How the work is done
- Remote 705 · 16%
- Hybrid 536 · 12%
- Onsite 377 · 9%
Visa sponsorship offered in 64% of the 1,033 postings that state a position on it.
Seniority
- Senior 1,235
- Staff 471
- Lead 222
- Principal 210
- Intern 114
- C-level 58
Who is hiring
- 1000+ employees 1,201
- 501-1000 employees 287
- 11-50 employees 125
- 51-200 employees 104
- 201-500 employees 27
- 1-10 employees 5
Artificial Intelligence Machine Learning Engineer
MANTECH seeks a motivated, career and customer-oriented Senior AI ML Engineer . This is currently a hybrid position with two to three days onsite in Ashburn, VA . In this role, you will collaborate within a…
Machine Learning Engineer
Build and deploy ML-powered features that improve customer experiences, from model training to production monitoring, using Python, TensorFlow/PyTorch, and managed services like Vertex AI.
Sr AI/ML Engineer local to St. Louis, MO
Builds and deploys LLM-powered agents/pipelines for field technicians, collaborating with platform architects to enhance multi-agent orchestration in production environments using Python, LangChain, and related tools.
ML Engineer
Builds and maintains ML models and data pipelines using Python, PySpark, Databricks, Kafka, and cloud tools like Azure and Snowflake.
Sr. Computer Vision Engineer (Deep Learning)
Design and deploy deep-learning perception models for ADAS in commercial EVs, optimizing neural networks for embedded automotive hardware.
Senior Software Engineer, AI/ML, Google Workspace
Build AI-powered productivity tools for Google Workspace (Gmail, Docs, Drive, etc.), designing ML systems that impact billions of users globally.
Staff Machine Learning Engineer
Build and ship production-grade AI systems—LLMs, agents, retrieval, and evals—from prototype to scalable deployment for high-stakes decision-making.
Machine Learning Engineer — Model Evaluation & Experimentation
Design and run ML experiments to evaluate and improve cutting-edge GenAI models, focusing on reinforcement learning tasks and rigorous analysis.
AI/ML Software Engineer
Develops real-time computer vision and AI algorithms for Apple products, integrating ML models into large-scale systems to power features like digital humans and health intelligence.
Mid AI/ML Engineer
Design and deploy AI/ML systems, including LLM-based and RAG architectures, for a federal data ecosystem while optimizing models and infrastructure on cloud platforms.
Applied Research Robotics & Computer Vision Engineer
Develops 3D computer vision and autonomous navigation systems for intelligent robots, implementing perception pipelines and scene reconstruction from monocular images.
Staff Machine Learning Engineer – (ADAS/Autonomous Driving)
Leads the integration and deployment of advanced perception models into production ADAS and autonomous driving systems, optimizing performance on automotive-grade hardware using C++, Python, CUDA, and TensorRT.
Machine Learning Engineer, Foundation Model Services
Build and optimize production-grade inference services for Apple’s large language, vision, and speech models, ensuring low-latency performance across products like Siri and Photos.
Senior Machine Learning Engineer
Build and scale AI systems—including generative AI, predictive models, and agentic workflows—using Python and cloud tools to automate commercial real-estate loan servicing at Berkadia.
Senior Machine Learning Engineer
Build and improve AI systems that power clinical products, including LLMs and agentic workflows, with end-to-end ownership of evaluation, deployment, and production debugging.