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Full Time Reinforcement Learning Jobs (NOW HIRING)

Keebo

Senior Machine Learning Engineer

$125K - $165K/yr

Familiarity with reinforcement learning or bandit models Nice to Have * Experience with Java and ... For full-time positions: * Competitive salary packages * Equity * Home office stipend

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All JobsFull Time Reinforcement Learning Jobs

Full Time Reinforcement Learning information

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$21K

$61.7K

$114.5K

How much do full time reinforcement learning jobs pay per year?

As of Jun 12, 2026, the average yearly pay for full time reinforcement learning in the United States is $61,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $72,000.00 per year, depending on experience, location, and employer.

What is the full meaning of full?

In the context of a full-time reinforcement learning job, 'full' refers to a work schedule that typically involves working around 40 hours per week, providing consistent employment and benefits. It indicates a commitment to a standard workweek rather than part-time or temporary roles. The term emphasizes the full scope of employment status in the job description.

What is the difference between Full Time Reinforcement Learning vs Data Scientist?

AspectFull Time Reinforcement LearningData Scientist
Required CredentialsAdvanced degree in CS, ML, or related field; experience with RL frameworksDegree in CS, Statistics, or related; strong programming and analytical skills
Work EnvironmentResearch labs, AI companies, tech firms focusing on RL projectsBusiness, tech companies, consulting firms analyzing data for insights
Industry UsageAI research, robotics, gaming, autonomous systemsFinance, healthcare, marketing, e-commerce, and more

Full Time Reinforcement Learning specialists focus on developing RL algorithms and models, often in research or AI product development. Data Scientists analyze data to extract insights and support decision-making across various industries. While both roles require strong technical skills, RL roles are more specialized in AI research and development, whereas Data Scientists have broader applications in data analysis and business strategy.

What is the meaning of full and fill?

In the context of a full-time reinforcement learning job, 'full' typically refers to working full hours per week, usually around 40 hours, while 'fill' is not directly related to employment terms. The focus is on the role's requirements, such as programming skills and understanding of machine learning algorithms, rather than these terms. If you encounter 'full' or 'fill' in job descriptions, clarify whether they refer to work hours or other specifics.

What is the synonym for full?

In the context of a full-time reinforcement learning role, the word 'full' is often synonymous with 'complete,' 'entire,' or 'whole,' indicating a position that requires working the standard full schedule, typically around 40 hours per week. This term emphasizes the comprehensive nature of the job commitment and responsibilities involved.
More about Full Time Reinforcement Learning jobs
What cities are hiring for Full Time Reinforcement Learning jobs? Cities with the most Full Time Reinforcement Learning job openings:
What are the most commonly searched types of Reinforcement Learning jobs? The most popular types of Reinforcement Learning jobs are:
What job categories do people searching Full Time Reinforcement Learning jobs look for? The top searched job categories for Full Time Reinforcement Learning jobs are:
Full Time Reinforcement Learning jobs near you
Infographic showing various Full Time Reinforcement Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $61,692 per year, or $29.7 per hour.
Senior Machine Learning Engineer - VLM/LLM Evaluation

Senior Machine Learning Engineer - VLM/LLM Evaluation

Waymo

Mountain View, CA • On-site

$204K - $259K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago

Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. 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 Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.
You will:
  • Work with a creative team of people who help to build the state-of-the-art Foundation Models that are used throughout Waymo's systems, both onboard autonomous vehicles and offboard in simulation
  • Drive the development or significantly contribute to end-to-end evaluation systems and benchmarks for Waymo Foundation models, encompassing the entire life-cycle from pre-training and supervised fine-tuning (SFT) to reinforcement learning (RL), for evaluating the quality, safety, and realism of embodied AI agents
  • Partner with cross-functional teams within the organization to land innovative tech in production
  • Implement and extend large large scale data and evaluation pipelines.

You have:
  • Bachelor or Master's degree in Computer Science, similar technical field of study, or equivalent practical experience
  • Experience in ML engineering and applied Deep Learning
  • Experience with large scale distributed system
  • Proficient programming skills (eg: Python, C/C++)

We prefer:
  • ML infra experience: training, evaluating and deploying ML models at scale
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning
  • Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$204,000-$259,000 USD

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