Research Engineer (Mountain View) 17813

Research Engineer

Location: Mountain View CA
Type: Full-time
Compensation: Competitive salary equity
Benefits: Health coverage ownership upside and direct collaboration with leading AI research organizations

About the Company

We are a fast-growing applied AI research lab focused on data and reinforcement learning (RL) environment curation for training and evaluating advanced agents.

Our work has powered state-of-the-art reasoning datasets specialized frontier models and multi-turn tool-using agents trained via reinforcement learning. Our research and systems are actively used by multiple top-tier AI labs and enterprise teams.

By combining deep research expertise with production-grade engineering we are building the infrastructure layer that enables the next generation of agent training. We are uniquely positioned to capture significant market share in data-centric AI and RL environment design.

The Role

We are seeking a Research Engineer to operate at the intersection of cutting-edge agent research and production-scale systems.

In this role you will work closely with frontier AI labs enterprise customers and internal research teams to design build and deploy high-quality RL environments at scale. Youll translate research insights into robust reproducible pipelines that directly impact how modern agents are trained and evaluated.

This position is ideal for someone who enjoys:

• Reading and implementing new research

• Prototyping novel ideas quickly

• Scaling research artifacts into production systems

• Working directly with highly technical external partners

You will have real ownership over systems that shape how next-generation agents learn.

What Youll Do

Research & Collaboration

• Partner with frontier AI labs to understand agent training requirements and design custom RL environments

• Stay current with advances in reinforcement learning agent training curriculum design and evaluation

• Prototype and validate new approaches to environment generation and data curation

• Translate academic research into scalable engineering solutions

Environment & Data Pipeline Engineering

• Build and maintain scalable pipelines for creating validating and deploying RL environments

• Design systems that ensure data quality diversity and reproducibility

• Implement automated QA and verification processes for environments

• Develop evaluation frameworks to measure environment effectiveness and training outcomes

Customer & Partner Engagement

• Work directly with enterprise customers to understand domain-specific agent challenges

• Customize environment suites benchmarks and evaluation setups for different use cases

• Provide technical guidance on best practices for agent training and evaluation

• Present research findings and system capabilities to technical stakeholders

Production Excellence

• Scale research prototypes into reliable production-ready systems

• Establish reproducible workflows and strong engineering standards

• Create documentation and tooling for internal teams and external users

• Monitor optimize and evolve systems as environment production scales

What Were Looking For

Research Background

• MS or PhD in Machine Learning Computer Science or a related field or equivalent industry research experience

• Demonstrated research contributions (publications open-source work or deployed research systems)

• Strong understanding of reinforcement learning agent training or related fields

• Ability to read implement and adapt ideas from recent research papers

Technical Execution

• Strong Python skills and experience with ML frameworks (e.g. PyTorch JAX)

• Experience building research infrastructure or production ML systems

• Familiarity with cloud platforms (AWS GCP) and distributed systems

• Systematic approach to testing validation and quality assurance

• Comfortable leveraging modern developer tools (e.g. AI-assisted coding workflows)

Collaboration & Communication

• Excellent communication skills across research and engineering teams

• Ability to translate research concepts into practical system requirements

• Strong project scoping prioritization and execution skills

• Comfortable presenting technical work to diverse highly technical audiences

Product & User Mindset

• Understanding of what makes research artifacts valuable in real-world use

• Experience shipping datasets benchmarks tools or platforms used by others

• Attention to documentation usability and long-term maintainability

• Customer-oriented approach to solving technical problems

Nice to Have

• Hands-on experience training or evaluating RL agents

• Background in data-centric AI synthetic data or dataset creation

• Publications at top-tier ML conferences (NeurIPS ICML ICLR etc.)

• Prior experience as a Research Engineer or Applied Scientist

• Contributions to widely used datasets benchmarks or evaluation suites

Why This Role

• Work directly with some of the most advanced AI research teams in the world

• Influence how next-generation agents are trained and evaluated

• Operate at the rare intersection of frontier research and production systems

• High ownership real-world impact and meaningful equity upside

Required Experience:

IC