Research Engineer

Bespoke Labs

Mountain View (CA)

On-site

USD 120,000 - 140,000

Full time

14 days+

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Benefits offered by this job

Health coverage

Opportunity to work with leading AI labs

Competitive salary and equity

Job summary

An AI research lab is seeking a Research Engineer responsible for bridging advanced research with production-scale development of reinforcement learning environments. The ideal candidate will have a strong background in machine learning, specifically in reinforcement learning, and experience with Python and ML frameworks. This role demands effective collaboration with research teams and enterprise customers to design custom environments, ensuring the successful deployment of high-quality solutions.

Qualifications

MS or PhD in Machine Learning, Computer Science, or equivalent industry research experience.
Track record of research contributions, such as publications or open-source projects.
Deep understanding of reinforcement learning and agent training.

Responsibilities

Partner with frontier AI labs to understand agent training needs.
Build scalable systems for creating and deploying RL environments.
Work directly with enterprise customers on their agent training challenges.

Skills

Python expertise

Reinforcement learning knowledge

Machine Learning frameworks experience

Excellent communication skills

Systematic approach to QA

Education

MS or PhD in Machine Learning or related field

Tools

PyTorch

AWS

GCP

Job description

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