Hybrid Research Engineer

at Bespoke Labs

• Job title: Research Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, Cloud, Google Cloud Platform, Python, PyTorch
• Location requirements: Hybrid, Mountain View, United States

About the role

• Research Engineer at Bespoke Labs bridging cutting-edge research with production-scale development of RL environments. Collaborating with frontier labs and enterprise customers to design training environments.

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

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
• 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
• Hands-on experience with RL agent training or evaluation systems (Nice to Have)
• Background in data-centric AI, synthetic data generation, or dataset creation (Nice to Have)
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, etc.) (Nice to Have)
• Previous experience in a research engineering or applied scientist role (Nice to Have)
• Contributions to widely-used datasets, benchmarks, or evaluation suites (Nice to Have)

Benefits

• Health coverage
• Opportunity to work directly with the world's leading AI research labs