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Remote Reinforcement Learning Jobs in California

Saga

Senior AI Engineer

Los Altos, CA · On-site +1

$123K - $169K/yr

We offer a flexible, remote working environment. You can expect a warm welcome from a friendly and ... Familiarity with reinforcement learning techniques (RLHF, reward modeling) or agent framework ...

Saga

Senior AI Engineer

Los Altos, CA · On-site +1

$123K - $169K/yr

We offer a flexible, remote working environment. You can expect a warm welcome from a friendly and ... Familiarity with reinforcement learning techniques (RLHF, reward modeling) or agent framework ...

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Remote Reinforcement Learning information

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.
What are the most commonly searched types of Reinforcement Learning jobs in California? The most popular types of Reinforcement Learning jobs in California are:
What are popular job titles related to Remote Reinforcement Learning jobs in California? For Remote Reinforcement Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Reinforcement Learning jobs in California look for? The top searched job categories for Remote Reinforcement Learning jobs in California are:
What cities in California are hiring for Remote Reinforcement Learning jobs? Cities in California with the most Remote Reinforcement Learning job openings:
Remote Reinforcement Learning jobs near you
Sr. Software Engineer, Simulation, tvScientific

Sr. Software Engineer, Simulation, tvScientific

Pinterest

San Francisco, CA • On-site, Remote

$144K - $190K/yr

Full-time

Re-posted 26 days ago

Job description

About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Sr. Software Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem - auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios - and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.
What you'll do:
  • Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
  • Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
  • Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
  • Use simulation to de-risk ML model deployments - validate new bidding and optimization strategies before they touch live traffic
  • Define the technical direction for simulation and AI infrastructure and mentor engineers on the team

What we're looking for:
  • Systems programming experience in Zig or similar (C, C++, Rust)
  • Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
  • Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows - and good judgment about when they help vs. when they don't
  • Adtech experience: you understand RTB mechanics, and the dynamics of programmatic advertising
  • Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
  • Clear written communication: you'll be defining new technical directions and need to bring others along
  • Ownership: you scope, design, and ship systems end-to-end with minimal direction
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
  • Bachelor's degree in computer science, machine learning, statistics, a related field or equivalent experience
  • Nice-to-Haves:
    • Strong production Python skills and experience building simulation or modeling systems
    • Causal inference - uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
    • Experience with discrete event simulation, Monte Carlo methods, or digital twins
    • Reinforcement learning - using simulated environments for policy learning and evaluation
    • Experience building agentic AI systems or multi-agent simulations
    • Big data experience with Scala and Spark
    • MLOps experience - model deployment, monitoring, and pipeline orchestration on AWS

In-Office Requirement Statement:
  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

Relocation Statement:
  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only
$155,584-$320,320 USD
Our Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.

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