Machine Learning / Reinforcement Learning Engineers (AI)

TL;DR

Machine Learning / Reinforcement Learning Engineers (AI): Designing, developing, and deploying sophisticated machine learning models for a platform handling complex, large-scale media-related data, with an accent on reinforcement learning frameworks and real-time processing. Focus on integrating AI models into core product features, rigorous experimentation, and contributing to foundational codebase and technical strategy.

Location: On-site in Los Angeles, CA

Salary: $200,000–$300,000 per year

Company

Our client is a high-growth, stealth-mode startup based in Los Angeles dedicated to reshaping the landscape of modern media.

What you will do

• Design, develop, and deploy sophisticated machine learning models, with emphasis on reinforcement learning.
• Architect scalable systems for real-time media data processing.
• Collaborate with a multidisciplinary team to integrate AI models into core product features.
• Conduct experimentation and optimization to improve model performance, stability, and efficiency.
• Contribute to the foundational codebase and technical strategy of a pre-launch platform.

Requirements

• Proven experience in Machine Learning, specifically within Reinforcement Learning, Deep Learning, or Neural Network architecture.
• A track record of tackling technically hard problems and delivering viable solutions under tight deadlines.
• Proficiency in Python and industry-standard ML frameworks (PyTorch, TensorFlow, JAX).
• Strong academic credentials in Computer Science, Mathematics, or a related field, complemented by significant professional contributions to AI-driven products.
• Ability to work in-person in Los Angeles.
• A driven, "A-player" mentality with the adaptability to thrive in a stealth-mode startup environment.

Culture & Benefits

• Highly competitive salary and significant early-stage equity packages.
• The chance to work alongside a concentrated team of elite engineers.
• High-energy, collaborative office setting in LA.
• Meaningful ownership in the company's long-term success.

Hiring process

• Initial Screening: Technical review of experience and previous projects.
• Deep-Dive Technical Assessment: Focused evaluation of Machine Learning and Reinforcement Learning competencies.
• Founder/Team Interview: Discussion regarding the vision of the startup, the stealth nature of the project, and cultural alignment.
• Final Review: Detailed discussion of compensation, equity, and the roadmap for the role.