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Learning Ai Jobs (NOW HIRING)

Gusto

Head of AI and Machine Learning Engineering

They are seeking a strategic Head of AI and Machine Learning Engineering to lead the development and implementation of AI/ML systems that enhance customer experiences and improve operational ...

Droyd Robotics

Machine Learning Intern

San Francisco, CA · On-site

Our AI team builds the models and inference systems that let robotic arms see, reason, and act. This work runs on deployed robots, not demos. About the role As a Machine Learning Intern at Droyd, you ...

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How much do learning ai jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for learning ai in the United States is $40.70, according to ZipRecruiter salary data. Most workers in this role earn between $29.57 and $52.88 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, machine learning executive, or senior data scientist, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These roles are usually found in large tech companies or startups with significant AI investments and may involve leadership, strategic planning, and cutting-edge development.

What is a Learning AI?

A Learning AI, or Artificial Intelligence that learns, refers to computer systems that can improve their performance over time by analyzing data and experiences. These systems use techniques such as machine learning and deep learning to adapt to new information, recognize patterns, and make predictions or decisions without being explicitly programmed for every task. Learning AI is used in many applications, including recommendation engines, language translation, and autonomous vehicles. As technology advances, Learning AI continues to play a crucial role in automating complex tasks and enhancing decision-making processes.

What jobs can I get if I learn AI?

Learning AI can qualify you for roles such as AI engineer, machine learning engineer, data scientist, or AI researcher. These positions typically require skills in programming, data analysis, and familiarity with AI frameworks like TensorFlow or PyTorch, and often involve developing algorithms, models, and applications across various industries.

What is the difference between Learning Ai vs Data Scientist?

AspectLearning AiData Scientist
Required CredentialsTypically a degree in Computer Science, AI, or related fields; certifications in AI/MLDegree in Computer Science, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness environments, analyzing data to inform decisions across industries
Employer & Industry UsagePrimarily in AI development, research, and product creationAcross finance, healthcare, marketing, and other sectors for data analysis

Learning Ai focuses on developing algorithms and models that enable machines to learn and improve autonomously, often involving deep learning and neural networks. Data Scientists analyze and interpret complex data to help organizations make informed decisions. While both roles require knowledge of machine learning, Learning Ai is more centered on creating AI systems, whereas Data Scientists focus on extracting insights from data.

Can I get paid to learn AI?

Learning AI can be financially supported through internships, apprenticeships, or training programs that offer stipends or salaries. Some companies and educational platforms also provide paid opportunities for gaining skills in AI, machine learning, and data science while working on real projects. However, most formal learning paths require self-investment or sponsorship until you acquire marketable skills for paid roles.

How do Learning AI professionals typically collaborate with subject matter experts to develop effective training solutions?

Learning AI professionals frequently work alongside subject matter experts (SMEs) to ensure that AI-driven training tools and content are accurate, relevant, and engaging. This collaboration often involves regular meetings to gather domain-specific knowledge, iterative review of training modules, and feedback sessions to fine-tune AI models for optimal learning outcomes. Clear communication and a strong partnership with SMEs are essential, as they help bridge technical AI capabilities with real-world educational needs, resulting in more impactful and user-friendly learning solutions.

How can I start a career in AI?

To start a career in AI, develop a strong foundation in mathematics, programming (especially Python), and machine learning concepts. Gaining experience through online courses, certifications, and projects using tools like TensorFlow or PyTorch can help build practical skills and improve employability in the field.

What are the key skills and qualifications needed to thrive as a Learning AI Engineer, and why are they important?

To thrive as a Learning AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or certification. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud computing platforms is typically required. Strong problem-solving skills, adaptability, and effective communication set outstanding professionals apart in this field. These skills are crucial for building, deploying, and refining AI models that solve real-world problems efficiently and ethically.
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What job categories do people searching Learning Ai jobs look for? The top searched job categories for Learning Ai jobs are:
Learning Ai jobs near you
Infographic showing various Learning Ai job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $84,648 per year, or $40.7 per hour.
Machine Learning Engineer - Reinforcement Learning

Machine Learning Engineer - Reinforcement Learning

pony.ai

Fremont, CA

$150K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago

Job description

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites around the world. Operating Robotaxi, Robotruck and Personally Owned Vehicles (POV) business units, Pony.ai is an industry leader in the commercialization of autonomous driving and is committed to developing the safest autonomous driving capabilities on a global scale. Pony.ai's leading position has been recognized, with CNBC ranking Pony.ai #10 on its CNBC Disruptor list of the 50 most innovative and disruptive tech companies of 2022. In June 2023, Pony.ai was recognized on the XPRIZE and Bessemer Venture Partners inaugural "XB100" 2023 list of the world's top 100 private deep tech companies, ranking #12 globally. As of August 2023, Pony.ai has accumulated nearly 21 million miles of autonomous driving globally. Pony.ai went public at NASDAQ in November 2024.

Responsibility
  • Build scalable systems for training and fine-tuning large generative models that produce realistic, informative driving behaviors for evaluation and scenario coverage.
  • Implement and iterate on RL-style methods: algorithms, reward / preference objectives, and training setups suited to high-fidelity, insightful behaviors in simulation-aligned workflows (closed-loop evaluation mindset).
  • Ship deep learning solutions (including LLM / VLM where appropriate) that improve human-led triaging, automate high-volume workflows, and support nuanced analysis of self-driving behavior to surface critical anomalies.
  • Own production-oriented ML for fleet-scale assessment: training, optimization, monitoring, and iteration of models used to judge performance across large real-world exposure.
  • Design and evolve data + evaluation systems inspired by RL from human preferences (RLHF) and related paradigms-turning preference/judgment signals into repeatable, scalable training and evaluation loops.
  • Partner broadly with teams such as Prediction, Planning, Research, and platform/engineering leads to land cross-cutting improvements with clear metrics.

Requirements

  • M.S. or Ph.D. in Computer Science, Machine Learning, AI, or a related field-or equivalent practical experience.
  • Hands-on experience building and applying ML in production-grade settings, with a strong RL component (policy learning, preference/feedback optimization, or offline/online RL pipelines).
  • Depth in deep learning, sequence modeling, and generative models.
  • Demonstrated impact via strong publications or a clear history of shipping impactful ML systems end-to-end.
  • Experience with large-scale distributed training and large-scale data processing.
  • Ability to lead ambiguous technical work from problem framing through reliable delivery.


Preferred
  • Background in autonomous vehicles, robotics, or complex simulation environments.
  • Strong grasp of modern RL and post-training techniques in LLM, dLLM, VLA and video generations.
  • Hands-on integration of simulation platforms with ML training and evaluation workflows.
  • Python fluency and frameworks such as PyTorch
  • Experience defining and operating metrics for complex, safety-critical AI systems.
  • Technical leadership: influencing stakeholders, aligning teams, and raising the bar for evaluation rigor.
  • Excellent communication-simple explanations of complex trade-offs.


Compensation and Benefits

Base Salary Range: $150,000 - $250,000 Annually

Compensation may vary outside of this range depending on many factors, including the candidate's qualifications, skills, competencies, experience, and location. Base pay is one part of the Total Compensation and this role may be eligible for bonuses/incentives and restricted stock units.

Also, we provide the following benefits to the eligible employees:

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (Traditional and Roth 401k)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Free Food & Snacks

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