Senior AI Research Engineer — RL & Synthetic Data Tools

Hidden Jobs; United States; Remote; USD 250,000 - 350,000; Full time

Benefits offered by this job

Equity

High autonomy

Collaboration with AI labs

Job summary

Hidden Jobs is seeking a senior role at the intersection of frontier AI research and practical engineering. You will help build large-scale datasets and reinforcement learning environments to advance model capabilities across domains such as software engineering, finance, and retail.

You will design experiments, prototypes, tooling, and evaluation frameworks, train and test models, and share findings through technical reports, workshops, or conference talks, while ensuring rigor and

Qualifications

• Candidates have strong research background in ML/AI.
• Proficiency with modern AI/ML tools for training and evaluation.
• Ability to design and analyze experiments from hypothesis to insight.
• Strong communication for cross-functional audiences.

Responsibilities

• Investigate capabilities, limitations, and training methods of advanced AI systems, formulating research questions that inform technical strategy.
• Design rigorous experiments, prototypes, tooling, and evaluation frameworks for synthetic and agentic data generation, reinforcement learning, and post-training.
• Train, test, and evaluate models using modern ML tools, drawing evidence-based conclusions from results.
• Collaborate across research, engineering, product, and operations teams to translate promising ideas into scalable real-world applications.
• Share findings through technical reports, open-source contributions, workshops, or conference participation.
• Establish practices for experimental rigor, reproducibility, and data quality across studies.

Skills

Strong research

AI/ML tooling

Experiment design

Cross-functional communication

Job description

Hidden Jobs is seeking a senior role at the intersection of frontier AI research and practical engineering. You will help build large-scale datasets and reinforcement learning environments to advance model capabilities across domains such as software engineering, finance, and retail.

You will design experiments, prototypes, tooling, and evaluation frameworks, train and test models, and share findings through technical reports, workshops, or conference talks, while ensuring rigor and