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Staff AI Scientist
Sin especificarTiempo completoAI & Machine LearningEnterprise SoftwareFinancial Software
Lead the research, design, and production implementation of foundation models and agentic systems for financial and business workflows. Set technical direction, advance applied AI research, and help deliver scalable intelligent products.
Responsabilidades
- Set technical strategy and roadmaps for foundation-model and agentic systems
- Design and develop foundational language models and agent architectures
- Research large-scale pretraining, supervised fine-tuning, reinforcement-learning fine-tuning, retrieval-augmented generation, and reasoning methods
- Build intelligent agents for bookkeeping, accounting, planning, communication, insights, and other business workflows
- Use financial and business data signals to improve model performance and defensibility
- Own experimentation, evaluation frameworks, metrics, and production delivery
- Mentor scientists and engineers and review technical designs
- Collaborate with research, engineering, product, and design teams
- Publish or present research and contribute to open-source frameworks where appropriate
Requisitos
- Master’s or doctoral degree in computer science, mathematics, machine learning, artificial intelligence, or a related field
- Technical leadership experience with complex AI systems
- Experience with large language models, multimodal models, or foundation models, including pretraining, fine-tuning, and deployment
- Deep understanding of transformer architectures, reinforcement learning, reasoning models, and agentic systems
- Strong Python proficiency and experience with modern machine-learning or agentic frameworks
- Experience building end-to-end AI pipelines from experimentation through production at scale
- Ability to influence technical direction across multiple teams and mentor scientists and engineers
- Strong problem-solving, collaboration, and communication skills
Se valora
- Experience with reinforcement-learning fine-tuning, including GRPO, RLHF, or RLFT
- Experience with model-based reinforcement learning for language or decision-making systems
- Background in financial, accounting, or business-domain AI
- Experience with probabilistic forecasting or world models
- Publications at leading machine-learning venues
- Meaningful open-source contributions
Beneficios
- Competitive compensation package
- Performance-based cash bonus eligibility
- Equity rewards eligibility
- Benefits under applicable company plans and programs