Staff Research Engineer - Frontier AI and Reinforcement Learning - International

Braintrust; Indonesia; Remote; IDR 390,600,000 - 725,400,000; Part time

Job summary

Braintrust is advancing frontier AI through rigorous research and engineering, focusing on synthetic and agentic data, reinforcement learning, and model evaluation. You will design experiments, build prototypes and scale validated findings into robust AI systems.

You will collaborate with Research, Engineering, Product and Operations, mentor engineers, and share results through reports, publications and open-source work.

Qualifications

• 7+ years of professional experience in ML research or frontier AI.
• PhD or master's in AI/ML/CS or equivalent research track.
• Strong ML foundations and experiment design.
• Research experience in synthetic/agentic data, RL, post-training, AI evaluation or tooling.
• Strong Python and ML tooling experience.
• Rigorous data quality and reproducible research methods.
• Excellent written and verbal communication and cross-functional collaboration.
• Mentoring engineers or researchers and providing technical leadership.

Responsibilities

• Investigate frontier-model capabilities, limitations and training methods, formulate research questions and explore new approaches.
• Build datasets, experiments, prototypes, tooling and evaluation frameworks. Train, test and evaluate models using modern ML tools.
• Analyze results with scientific rigor, data quality, reproducibility and evidence-based interpretation. Iterate from hypotheses to validated insights.
• Collaborate across Research, Engineering, Product and Operations to translate findings into practical systems.
• Communicate findings through technical reports, publications, open-source work and research forums; contribute through peer review and mentorship.

Skills

Python programming

ML frameworks

Research leadership

Experiment design

Cross-functional collaboration

Education

PhD or Master’s in AI/ML/CS

Tools

PyTorch

TensorFlow

Jupyter

Job description

Advance frontier AI through research and engineering across synthetic and agentic data, reinforcement learning, post-training, model understanding, benchmarks and evaluation. You will investigate high-impact questions, build research-grade prototypes and help turn validated findings into scalable AI systems.

What You Will Do

• Investigate frontier-model capabilities, limitations and training methods, formulate research questions and explore new approaches.
• Build research datasets, experiments, prototypes, tooling and evaluation frameworks. Train, test and evaluate models using modern ML tools.
• Analyze results with scientific rigor, data quality, reproducibility and evidence-based interpretation. Iterate from hypotheses to validated insights.
• Collaborate across Research, Engineering, Product and Operations to translate findings into practical systems.
• Communicate findings through technical reports, publications, open-source work and research forums where appropriate. Contribute through peer review, mentorship and technical leadership.

What You Will Bring

• 7+ years of professional experience with significant research engineering experience in machine learning or frontier AI systems.
• A PhD or master’s degree in AI, machine learning, computer science or a closely related technical field, or exceptional equivalent research experience.
• Strong ML foundations and experience designing experiments, training or evaluating models, or developing AI systems.
• Research experience in at least one of synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, or tool-using AI agents.
• Strong Python programming and experience implementing, testing and iterating with modern ML frameworks and tooling.
• Scientific judgment, rigorous reproducible methods and attention to data quality.
• Strong written and verbal communication, independent work and effective cross-functional collaboration.
• Experience mentoring engineers or researchers and providing technical leadership.

PROJECT DETAILS

Expected project length is three months, with an immediate start. Availability of at least 40 hours per week, 8 hours per day and four hours of daily Pacific Time overlap is required. Selection includes an approximately 20-minute client AI interview and a 45-60-minute technical delivery interview. Include your LinkedIn profile URL in your required resume.