Research Engineer

Bespoke Labs•Mountain View, CA

12h•Onsite

About The Position

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.

Requirements

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
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.
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
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 Haves

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

Responsibilities

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.
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
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
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