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Remote Reinforcement Learning Jobs (NOW HIRING)

Keebo

Senior Machine Learning Engineer

$125K - $165K/yr

Experience with Reinforcement Learning * Experience with Google Cloud and BigQuery Our Environment Keebo is a fully remote, global team with team members currently in the US, EU, and Canada. What we ...

DocuSign

Senior Machine Learning Engineer

Seattle, WA · On-site +1

$186K - $300K/yr

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL ... Employee divides their time between in-office and remote work. Access to an office location is ...

DocuSign

Senior Machine Learning Engineer

San Francisco, CA · On-site +1

$186K - $300K/yr

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL ... Employee divides their time between in-office and remote work. Access to an office location is ...

DocuSign

Senior Machine Learning Engineer

Seattle, WA · On-site +1

$186K - $300K/yr

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL ... Employee divides their time between in-office and remote work. Access to an office location is ...

Zillow

Principal Machine Learning Engineer, Agentic AI

$194K - $310K/yr

They'll be developing perception and language understanding, deep reasoning, and reinforcement ... This role has been categorized as a Remote position. "Remote" employees do not have a permanent ...

Vantor

Staff Applied AI Engineer

... optimization, reinforcement learning, and heuristic approaches • Map system complexity and ... enable remote mission operations and dramatically reduce planning cycle times Qualifications

Zillow

Principal Applied Scientist, Agentic AI

$181K - $290K/yr

We collaborate closely with platform, product, and operations partners in a fast-moving, remote ... You are an applied scientist who is excited to use reinforcement learning and post-training methods ...

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All JobsRemote Reinforcement Learning Jobs

Remote Reinforcement Learning information

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$11K

$83.9K

$140K

How much do remote reinforcement learning jobs pay per year?

As of Jul 3, 2026, the average yearly pay for remote reinforcement learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a Remote Reinforcement Learning job?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

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

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What is the difference between Remote Reinforcement Learning vs Remote Machine Learning Engineer?

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

What are common challenges faced when working remotely in a Reinforcement Learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.
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Remote Reinforcement Learning jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Keebo

Remote

$125K - $165K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

Keebo is a venture-backed startup that offers a turnkey cloud-based Data Learning platform for automating and accelerating enterprise analytics. With the data warehousing market expected to grow to $51B annually by 2028, Keebo is an industry innovator, as the only fully-automated Snowflake optimizer, adjusting dynamically to save many customers 25% and more.
Built on state-of-the-art in machine learning and artificial intelligence, and over 15 years of cutting-edge research at top universities, Keebo reduces tedious and months-long manual operations to a matter of minutes, freeing up data teams to work on improving their core business. Our team is spread across the globe, supporting customers worldwide.
About the Opportunity
As a Senior Machine Learning Engineer, you will bring your expertise in machine learning and data science to help the team move faster and achieve critical revenue goals for Keebo. You will work closely with ML engineers and data engineers to evaluate algorithmic and business problems and apply your machine learning and software engineering skills to build reliable, repeatable models that run in production with high quality.
You Will
  • Research, implement, and tune cutting-edge RL/ML models to achieve critical business outcomes
  • Design and implement AI/ML models that balance quality, speed, and cost
  • Collaborate with the rest of the Algorithms team to achieve goals that drastically impact the revenue of the business
  • Build repeatable, reliable pathways for promoting ML models from development to production

You Have
  • Experience as a machine learning engineer, working on real-world problems impacting live customers
  • Experience developing ML models end to end and deploying into production environments
  • Experience building and maintaining scalable, reliable, and safe ML models that directly impact customers' experience
  • Experience implementing AI/ML models that balance quality, speed, and cost
  • Experience automatically monitoring the quality and effectiveness of ML/AI models from local dev through to production
  • Experience with SQL, data analysis, and databases
  • Experience with Python, and strong track record of writing readable, maintainable production code
  • Experience with GCP or AWS
  • Skilled in being self-directed and moving quickly to build and improve systems and architectures
  • Ability to work in a fast-paced early stage startup
  • Skilled at communicating effectively in a distributed environment with people across multiple time zones
  • Strong self-motivation, initiative, and adaptability
  • Familiarity with reinforcement learning or bandit models

Nice to Have
  • Experience with Java and Golang
  • Experience with Reinforcement Learning
  • Experience with Google Cloud and BigQuery

Our Environment
Keebo is a fully remote, global team with team members currently in the US, EU, and Canada.
What we Offer
Working with a world-class team of researchers and engineers in machine learning to turn Al algorithms into scalable and automated cloud products
For full-time positions:
  • Competitive salary packages
  • Equity
  • Home office stipend
  • Comprehensive medical, dental, and vision benefits
  • 401k retirement program
  • Annual company offsite (this year the team met up in Cancún, Mexico!)
  • Paid time off
  • Paid parental leave

Keebo is proud to be an equal opportunity employer and prohibits discrimination and harassment of any kind. We are committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, gender, national origin, age, disability, genetic information, or any other protected characteristic. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We strive to create a diverse and inclusive workplace where everyone feels valued and respected. We encourage individuals from all backgrounds to apply.

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