Entrepreneurial AI Researcher

About This Opportunity

We are representing a confidential quantitative finance organization that is building foundational AI models for specialized applications. Our talent team is seeking an Entrepreneurial AI Researcher to join a small, high-velocity research team working on novel problems at the intersection of machine learning and financial data.

This is a remote position offering deep autonomy and the opportunity to pursue original research agendas from concept through production deployment.

Responsibilities

• Formulate and execute original research agendas in areas including reasoning, tool connectivity, robustness, alignment, and data/compute efficiency
• Own the complete research lifecycle: from initial ideas through proof-of-concept, MVP development, training, and validation
• Build rigorous evaluation suites using simulated environments and real-time assessment methods
• Prototype rapidly with real datasets and collaborate closely with research engineers to transition promising concepts to production systems
• Develop efficient training methods and explore reasoning, tool use, and multimodal learning approaches
• Set research direction and technical standards for the team

What We're Looking For

Required skills and experience:

• Self-starter who thrives with coding autonomy in small-team, high-velocity environments
• Strong machine learning research foundation combining theoretical depth with practical implementation skills
• Proficiency writing clean, reproducible code in PyTorch or JAX
• Systems thinking that encompasses data quality, scaling laws, evaluation frameworks, and deployment constraints
• Collaborative approach with clear principles and low ego

Helpful backgrounds (any of the following):

• Experience at frontier AI labs
• Published research at venues such as NeurIPS, ICML, or ICLR
• Led research in applied settings including startups, open-source projects, or production systems at scale
• Standout independent achievements such as notable open-source contributions, benchmarks, or widely adopted methods

Research areas of particular interest:

• Efficient training methods (hierarchical reinforcement learning, distillation, sparse/MoE architectures, FSDP)
• Reasoning and tool use for automated systems and agentic data interaction
• Multimodal inputs and outputs including text and time-series data

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and research interests. Qualified candidates are then presented to our client for consideration. Please do not attempt to contact the client organization directly, as all communication is coordinated through our talent team to ensure a smooth process for everyone involved.

Pay

Compensation details will be discussed during the screening process and are competitive within the quantitative finance and AI research space, including base salary and performance-based upside tied to research impact.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices and works with clients who value diverse perspectives and backgrounds in building their teams.