AI-Native ML Engineer: RL Systems & Research Impact (Equity)

Verita Ai; San Francisco (CA); On-site; USD 200,000 - 250,000; Full time

Job summary

Verita AI is seeking an “AI-native” Machine Learning Engineer to join our core engineering team in San Francisco. This role blends research and product work, building robust RL environments and iterating on automation to scale with high quality standards.

You will collaborate closely with researchers and product teams to translate hypotheses into verifiable implementations, delivering reliable RL pipelines, deployment-ready tooling, and scalable data workflows that power our Foundry and Studio

Qualifications

• Demonstrated experience building, managing, and troubleshooting reinforcement learning environments end-to-end.
• Hands-on experience with containerized RL environments and framework integration ( Harbor framework ).
• Practical experience building and implementing verifiers for RL models to ensure consistent, verifiable reward signals.
• Proficiency in modern reward functions and optimization (PPO, DPO, GRPO).
• Expertise in designing and maintaining quality control (QC) pipelines for RL and synthetic data.
• Proven ability to work in a pair-programming or highly collaborative team setting, specifically with researchers, operations stakeholders, and product owners to cross-verify ideas and iteratively improve model performance.

Responsibilities

• Build robust RL environments and iterate rapidly on new product automations.
• Collaborate closely with researchers and product builders to translate high-level hypotheses into concrete, verifiable implementations.
• Develop scalable RL workflows and tooling to support research and production integration.

Skills

RL Environment Proficiency

Containerized RL

Verifiable Rewards (RLVR)

Optimization Methodologies

QC Pipelines

Collaborative Mindset

Tools

Harbor framework

Job description

Verita AI is seeking an “AI-native” Machine Learning Engineer to join our core engineering team in San Francisco. This role blends research and product work, building robust RL environments and iterating on automation to scale with high quality standards.

You will collaborate closely with researchers and product teams to translate hypotheses into verifiable implementations, delivering reliable RL pipelines, deployment-ready tooling, and scalable data workflows that power our Foundry and Studio