Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading digital bank in Latin America serves more than 135 million customers across Brazil, Mexico, and Colombia. The organization is transforming the financial services industry through data and proprietary technology, developing innovative products and services designed to improve financial access and advancement.
People & Team Leadership
- Lead, mentor, and advocate for a team of highly accomplished machine learning researchers.
- Foster an environment characterized by psychological safety, high ambition, collaboration, and rigorous scientific inquiry.
- Own team operating health, including performance management, career development, hiring, and compensation cycles.
- Attract and retain top-tier research talent in a highly competitive market.
- Build a strong reputation for the research team as an environment where exceptional researchers can thrive.
- Support highly autonomous individual contributors operating at staff-level and above technical depth.
Research Operations & Execution
- Own the operating cadence of two to three concurrent, quarter-scale research initiatives.
- Guide research initiatives from problem framing and OKR development through progress tracking and go/no-go decisions.
- Allocate scarce and high-value resources, particularly GPU capacity, across competing research priorities.
- Balance exploratory research with initiatives that have the strongest potential for long-term impact.
- Protect deep-focus research time to enable rigorous, multi-quarter scientific work.
- Raise standards for experimental design, peer review, research communication, and reproducibility.
- Encourage publishing, open-source contributions, and conference participation that strengthen the team’s research reputation and support talent attraction.
Strategy & Cross-Team Collaboration
- Partner closely with senior technical leaders responsible for architecture and scientific direction.
- Align operational execution with the long-term machine learning research roadmap.
- Ensure scientific and operational decisions reinforce one another.
- Establish effective handoffs from research into production so breakthrough results can be reproduced and adopted by applied teams.
- Translate complex technical developments, including training efficiency, causal inference, and novel architectures, into clear narratives for executive leadership.
- Connect research milestones with measurable business outcomes.
- Bridge foundational research with long-term business strategy and the organization’s AI-first direction.
Required Qualifications
- 3+ years of direct people-management experience leading applied AI research or core machine learning teams within large technology companies, frontier research organizations, or comparable high-scale environments.
- M.S. or Ph.D. in Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
- Strong working knowledge of core artificial intelligence and machine learning methodologies.
- Proven ability to build, scale, and retain high-performing research or advanced applied-science teams.
- Experience managing highly autonomous researchers and technical professionals.
- Demonstrated ability to operate effectively at the intersection of advanced AI research and applied machine learning.
Preferred Qualifications
- Deep conceptual knowledge of at least one core research area, including:
- Foundation models and LLMs, including pre-training, scaling laws, training optimization, and large GPU-cluster workflows.
- Behavioral and sequential models, recommendation systems, and large-scale representation learning.
- Decisioning and optimization, including causal inference, policy optimization, constrained optimization, or reinforcement learning.
- Training and inference efficiency, including model sparsification, quantization, distillation, parallelism, and partitioning.
- Exceptional storytelling and communication skills, with experience translating complex technical achievements into business impact for senior and C-level audiences.
- Experience working within global and distributed teams.
- Experience moving foundational research into scalable, production-grade systems.
- Strong understanding of how to balance long-term research objectives with immediate business priorities.
Disclaimer
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