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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?

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?

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

Staff Product Manager, AI Safety

Pinterest

San Francisco, CA • On-site, Remote

Full-time

Re-posted 10 days ago

Job description

As a Staff Product Manager for the GenAI Safety team within Trust & Safety, you'll define and drive the product strategy for ensuring Pinterest's GenAI-powered systems are safe, fair, and trustworthy. You'll be responsible for building proactive safety frameworks that scale with our growing AI capabilities, partnering deeply with engineering, policy, data science, and design to protect our users while enabling Pinterest to innovate responsibly.

This is a high-impact role for someone who is passionate about the intersection of AI and user safety, and who thrives in ambiguous, fast-evolving problem spaces. You'll work at the frontier of responsible AI - anticipating novel harms before they emerge, red-teaming new AI features, and translating complex policy goals into measurable product requirements.

What you'll do:

  • GenAI Safety Strategy: Own and drive the product roadmap for GenAI safety across Pinterest's AI-powered surfaces, including assisted search, content recommendations, automated moderation, and generative content creation tools
  • Threat Modeling & Red-Teaming: Lead proactive identification of risks, failure modes, and adversarial attack vectors across AI systems - designing structured red-teaming exercises and evaluation frameworks before and after product launches
  • Policy-to-Product Translation: Partner closely with Trust & Safety policy, legal, and ethics teams to translate nuanced content guidelines (e.g., self-harm, misinformation, body image) into precise, buildable product requirements and model guardrails
  • Cross-Functional Collaboration: Work with engineering, ML, design, data science, policy, legal, comms, and operations teams to define, align, and ship AI safety solutions across global markets and diverse user populations
  • Evaluation & Measurement: Define and track quantitative safety metrics - including fairness audits, false positive/negative rates, disparate impact analysis, and content harm reduction - to ensure AI systems meet safety standards at scale
  • Incident Response: Develop and maintain AI safety incident runbooks and escalation frameworks, and lead rapid triage and remediation when AI systems produce harmful or unexpected outputs
  • Emerging Risk Anticipation: Stay ahead of the rapidly evolving AI landscape to identify safety implications of new capabilities (e.g., multi-modal generation, synthetic media, agentic AI) and proactively build extensible safety infrastructure to address unknown future applications
  • Global & Cultural Sensitivity: Ensure AI safety approaches account for the needs, norms, and contexts of Pinterest's diverse global user base - avoiding one-size-fits-all solutions and centering equity in safety design
  • User & Employee Wellbeing: Champion the safety and psychological wellbeing of both users who encounter harmful content and internal teams (content reviewers, T&S specialists) who work on the front lines of content safety

What we're looking for:

  • 7+ years of product management experience, with meaningful depth in GenAI/ML, trust & safety, content moderation, or responsible AI
  • Strong fluency in AI/ML concepts - including generative models, recommendation systems, multi-modal AI, and reinforcement learning from human feedback (RLHF)
  • Experience with AI ethics frameworks, responsible AI principles, or relevant regulatory landscapes (e.g., NIST AI RMF, EU AI Act)
  • Demonstrated ability to lead cross-functional teams through ambiguous, high-stakes problem spaces with a bias for action
  • Proficiency in engaging with research, mapping threat models, validating risks, and translating insights into clear product strategies and roadmaps
  • Excellent communication skills - the ability to articulate complex technical and ethical trade-offs to non-technical audiences and senior leadership, facilitating clear decision-making
  • Deep empathy for users and a genuine commitment to making the internet safer
  • Bachelor's degree in a relevant field such as Computer Science, or equivalent experience

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

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