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Reinforcement Learning Engineer Jobs in Reseda, CA

Spotter

Machine Learning Scientist

Culver City, CA · On-site

Collaborating closely with Product and Engineering to translate customer problems into machine learning solutions. * Staying current with advances in reinforcement learning, bandits, recommendation ...

Spotter

Machine Learning Scientist

Culver City, CA · On-site

Collaborating closely with Product and Engineering to translate customer problems into machine learning solutions. * Staying current with advances in reinforcement learning, bandits, recommendation ...

YO AI Labs

Backend Engineer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

YO AI Labs

AI Engineer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

YO AI Labs

AI Software Engineer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Paramount

Lead Machine Learning Engineer

Burbank, CA · On-site

$109K - $143K/yr

... and reinforcement learning. High-Performance Inference: Design and maintain K8s-based inference ... Reliability Engineering: Define and enforce SLIs/SLOs for the platform, ensuring that ...

YO AI Labs

Backend Developer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

... Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning ...

Paramount

Lead Machine Learning Engineer

Burbank, CA · On-site

$109K - $143K/yr

... and reinforcement learning. High-Performance Inference: Design and maintain K8s-based inference ... Reliability Engineering: Define and enforce SLIs/SLOs for the platform, ensuring that ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Reseda, CA

Reinforcement Learning Engineer information

See Reseda, CA salary details

$40.8K

$124.5K

$205.8K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for reinforcement learning engineer in Reseda, CA is $124,534.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,200.00 and $162,800.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

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

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What job categories do people searching Reinforcement Learning Engineer jobs in Reseda, CA look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Reseda, CA are:

What cities near Reseda, CA are hiring for Reinforcement Learning Engineer jobs?

Cities near Reseda, CA with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Reseda, CA as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $124,534 per year, or $59.9 per hour.

Senior Machine Learning Engineer - Platform and Integrations

WorkGenius Group

Santa Monica, CA • On-site

$137K - $181K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Title: Senior Machine Learning Engineer - Platform and Integrations
Industry: Gaming
Location: Santa Monica, CA
Duration: 12 months
Responsibilities
  • Build and operate distributed ML training systems across multi-node GPU clusters and scale game simulation environments for parallel rollouts, data collection, and policy evaluation.
  • Develop automated ML pipelines supporting data and model versioning, validation, experiment tracking, and governance.
  • Build and optimize inference-serving systems for latency, cost, accuracy, and reliability.
  • Create developer tools, SDKs, and templates that streamline the ML development lifecycle.
  • Monitor system health, troubleshoot production issues, improve performance, implement security controls, and mentor engineers.
Requirements
  • Bachelor’s degree in Computer Science or a related field, or equivalent experience, with 3+ years of software engineering experience in ML, platform, or systems engineering.
  • Experience operating distributed systems and production GPU workloads, including distributed machine learning or agent training using reinforcement learning or imitation learning.
  • Strong Python skills, working knowledge of C++, and experience with PyTorch, Ray or RLlib, and multi-node GPU orchestration.
  • Ability to work across ML training, evaluation, inference, and infrastructure, with experience in resource optimization, model evaluation, or ML governance.
  • Strong technical communication and documentation skills; experience with game AI, game simulation, Unreal Engine, real-time interactive environments, or self-service ML platforms is desirable.
Skills
  • Distributed ML
  • GPU Clusters
  • Reinforcement Learning
  • Imitation Learning
  • PyTorch
  • Python
  • C++
  • Ray/RLlib
  • Inference Serving
  • ML Platform Engineering
Hourly rate is commensurate with experience and is an estimated range provided by WorkGenius.
ref_id: a21a2dc1-94ee-4825-8b7e-012354402584

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