Applied AI Research Scientist
AI risk platform that helps financial institutions prevent fraud, ensure compliance, and detect money laundering through behavioral analysis and device intelligence.
Maintainer signals as of 9/2/2026
Funding history
Projects
About Sardine
Sardine helps financial institutions prevent fraud and ensure compliance by analyzing user behavior and device intelligence in real-time. Users can detect identity theft, payment fraud, account takeovers, and money laundering while streamlining KYC/AML processes. Sardine provides risk management with AI agents, case management, and regulatory reporting tools.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will identify research opportunities, design experiments, and drive foundation model development. You will establish evaluation standards, prepare data, pretrain and adapt models, and deploy them for low-latency inference. You will also support production infrastructure, explain model capabilities to customers, and develop documentation and governance for regulated financial use cases.
Requirements
- 4+ years of experience in applied machine learning, quantitative modeling, or ML engineering
- Experience pretraining or substantially adapting and deploying at least one foundation model
- Hands-on self-supervised pretraining, fine-tuning, and model adaptation experience
- Production experience with model serving, versioning, monitoring, and rollback
- Ability to manage ambiguous applied research projects and communicate clearly across functions
- Strong Python and SQL skills
- Experience preparing very large datasets
- Background in fraud, AML, payments, credit, or adversarial machine learning
- Experience building and evaluating LLM-based agents in production
- Publications, released models, or open-source contributions in representation learning or sequence modeling
- Experience with model risk management and documentation in a regulated financial environment
Responsibilities
- Identify research opportunities and execute the foundation model roadmap
- Design experiments and evaluate models with rigorous benchmarks and holdouts
- Prepare data and tokenization pipelines
- Pretrain, fine-tune, distill, quantize, and deploy models
- Partner on training infrastructure, GPU efficiency, feature stores, embedding stores, and model serving
- Translate model capabilities and limitations into actionable risk decisions
- Develop explainability, documentation, and governance for regulated customers
Benefits
- Equity compensation
- Early exercise for all options including pre-vested options
- Remote-first work from anywhere
- Flexible paid time off
- Year-end break
- Health insurance, dental, and vision coverage for employees and dependents in the US and Canada
- 4% 401k or RRSP matching in the US and Canada
- MacBook Pro
- One-time home office setup stipend
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual learning stipend