Research Engineer

About Bespoke Labs

Bespoke Labs is an applied AI research lab pioneering data and RL environment curation for training and evaluating agents.

Recently, we curated Open Thoughts , one of the best open reasoning datasets used by multiple frontier labs, trained SOTA specialized models such as Bespoke-MiniChart-7B and Bespoke-MiniCheck , and taught agents to do multi-turn tool-calling with reinforcement learning.

Bespoke is uniquely positioned to capture a large market share of data and RL environment curation.

About The Role

We're looking for a Research Engineer to bridge cutting-edge research with production-scale development and deployment of RL environments. You'll work at the intersection of research and engineering—collaborating with frontier labs and enterprise customers to understand their needs, then translating those insights into systematic environment creation.

This role requires both research depth and execution excellence. You'll need to understand the latest advances in agent training, communicate effectively with research teams at top labs, and build robust systems that deliver high-quality environments at scale. You're equally comfortable reading papers, prototyping novel approaches, and shipping production pipelines.

You'll work closely with both external collaborators (frontier labs, enterprise partners) and internal teams to ensure our research insights translate into valuable products that advance the state of agent training.

What You'll Do

Research & Collaboration

Partner with frontier AI labs to understand their agent training needs and design custom environments.

Stay current with latest research in RL, agent training, and evaluation methodologies.

Prototype novel approaches to environment generation, curriculum design, and data curation.

Translate academic insights into practical engineering solutions.

Environment & Data Pipeline Development

Build and maintain scalable systems for creating, validating, and deploying RL environments

Develop systematic approaches to data curation that ensure quality and diversity

Create automated quality assurance pipelines for environment verification

Design evaluation frameworks that measure environment effectiveness

Customer Engagement

Work directly with enterprise customers to understand their specific agent training challenges

Customize environment suites and benchmarks for different use cases and domains

Provide technical guidance on best practices for agent training and evaluation

Present research findings and product capabilities to technical stakeholders

Production Excellence

Scale research prototypes into production-ready systems that handle large-scale deployment

Establish reproducible workflows and maintain high engineering standards

Create documentation and tools that enable both internal teams and external users

Monitor and optimize system performance as we scale environment production

What We're Looking For

Research Background

MS or PhD in Machine Learning, Computer Science, or related field, OR equivalent industry research experience

Track record of research contributions (publications, open-source projects, or deployed research systems)

Deep understanding of reinforcement learning, agent training, or related areas

Ability to read and implement ideas from recent papers

Technical Execution

Strong Python skills and experience with ML frameworks (PyTorch, JAX, or similar)

Experience building production systems or research infrastructure at scale

Proficiency with cloud platforms (GCP, AWS) and distributed computing

Systematic approach to testing, validation, and quality assurance

Ability to use modern tools such as Claude Code effectively.

Collaboration & Communication

Excellent communication skills for working with research teams and enterprise customers

Experience translating between research concepts and practical requirements

Ability to scope projects, set priorities, and deliver on commitments

Comfortable presenting technical work to diverse audiences

Product Mindset

Understanding of what makes research artifacts valuable to users

Experience shipping products, datasets, or tools used by others

Attention to detail in documentation, usability, and user experience

Customer-focused approach to problem-solving

Nice to Have

Hands-on experience with RL agent training or evaluation systems

Background in data-centric AI, synthetic data generation, or dataset creation

Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, etc.)

Previous experience in a research engineering or applied scientist role

Contributions to widely-used datasets, benchmarks, or evaluation suites

Logistics

Location: Mountain View, CA

Compensation: Competitive salary and equity

Benefits: Health coverage, and the opportunity to work directly with the world's leading AI research labs