---
title: 'Applied AI Research Scientist at Sardine'
canonical: 'https://feeny.ai/job/applied-ai-research-scientist-sardine-north-fngvcne22ceb'
type: 'job'
last_seen: '2026-09-05'
---

# Applied AI Research Scientist at Sardine

- **Company:** Sardine
- **Location:** North, United States
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-09-04
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.ashbyhq.com/sardine/44cf5225-547a-4584-a271-c0c6ddc7b0b6

## Job description

Who we are:

Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products.

Our culture:

- We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere
- We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
- We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.

Location:

- Remote -United States or Canada
- From Home / Beach / Mountain / Cafe / Anywhere!
- We are a remote-first company with a globally distributed team. So you can find your productive zone and work from there.

## About the role

Sardine sits on one of the richest behavioral datasets in fraud and risk: device intelligence, behavior biometrics, session telemetry, payment events, and consortium signals that we leverage to fight fraud across hundreds of fintechs and banks. We are looking for an applied research scientist that brings their expertise in deep learning and foundation models to take this to the next level.

We are looking for an experienced ML applied scientist that can combine foundation model expertise with rich non-text sequential data to come up with practical, state-of-the-art fraud detection solutions. You will have an opportunity to scope and drive the next generation of fraud foundation models at Sardine, and drive industry-wide adoption.

## What you'll be doing

- Identify and scope opportunities, design rigorous experiments, and execute on the roadmap for foundation model research and development.
- Own the evaluation bar for foundation model performance: offline benchmarks, time- and entity-aware holdouts, calibration, drift and degradation monitoring, and honest head-to-head comparisons against strong classical baselines.
- Take models the full distance from data prep and tokenization through pretraining, fine-tuning, distillation, quantization, and deployment behind a real-time inference path with tight latency budgets.
- Partner with Engineering on training infrastructure, GPU efficiency, feature and embedding stores, and serving at production scale
- Work directly with client-facing teams and customers to turn model capabilities and limits into decisions their risk teams can act on.
- Partner with Legal, Compliance, and customer model risk teams to build the explainability, documentation, and governance our bank and fintech customers need to satisfy their own regulators.

## What you'll need

- 4+ years in applied machine learning, quantitative modeling, or ML engineering including at least one foundation model you pre trained or substantially adapted and put in front of real traffic
- Hands-on self-supervised pre training experience, plus practical fine-tuning and adaptation
- Production experience with model serving, versioning, monitoring, and rollback
- Ability to self-manage and drive ambiguous applied research projects with clear communication with partner teams across data science, engineering, product, marketing and external partners
- Strong Python, strong SQL, and comfort preparing very large datasets

Nice to haves

- 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

Benefits we offer:

- Generous compensation in cash and equity
- Early exercise for all options, including pre-vested
- Work from anywhere: Remote-first Culture
- Flexible paid time off and Year-end break
- Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
- 4% matching in 401k / RRSP - US and Canada specific
- MacBook Pro delivered to your door
- One-time stipend to set up a home office — desk, chair, screen, etc.
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual Learning stipend

Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.

To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our Applicant and Worker Privacy Notice https://www.sardine.ai/applicant-and-worker-privacy-notice.

## About Sardine

## Company Overview
- **One-liner**: Sardine provides an agentic risk platform that uses AI to help banks, fintechs, and merchants detect fraud, automate AML compliance, and fight financial crime from a single unified system.
- **Entity Type**: Private (has raised $170 million in funding)
- **Headquarters**: Remote-first; specific headquarters city not publicly disclosed in available sources
- **Founded**: Year not publicly available in the provided sources
- **Founders**: Soups Ranjan (CEO, Co-Founder)

## Core Business
- **Primary Industries**: Fraud prevention, AML compliance, financial crime detection, risk intelligence, cybersecurity
- **Target Customers**: B2B – banks, fintechs, marketplaces, merchants (enterprise and mid-market)
- **Mission or Purpose**: Help teams stop fraud earlier, protect customers better, and move with confidence as the financial system evolves – using AI that is transparent, explainable, and works alongside human judgment.

## Products & Services
- **Fraud Prevention**: Real-time, behavior-based fraud detection using device intelligence, behavioral biometrics, and proprietary signals to catch scams and fraud without adding friction.
- **AML Compliance**: Automated KYC/AML alert reviews, sanctions screening, PEP exposure, adverse media monitoring, and transaction monitoring to detect money laundering and mule activity.
- **Agentic AML Ops & Agentic Fraud Ops**: AI agents that automate data analysis, alert reviews, and investigations, helping risk teams become 10x more effective.
- **Identity Verification (KYC/KYB)**: Global identity verification for consumers and businesses, including synthetic ID detection, deepfake prevention, and business beneficial owner authentication.
- **Case Management**: Unified workspace to review alerts, conduct investigations, and resolve cases with audit-ready outputs.
- **Customer Risk Rating**: Tiers customers by risk level to support CDD and ongoing compliance.
- **Credit Underwriting**: Build, test, and deploy credit models without engineering support.
- **Bank Verification**: Validate bank account ownership and risk levels in real-time.
- **Sonar Consortium Network**: Shared anonymized risk intelligence across fintech, banking, and commerce to expose fraud patterns no single organization can see alone.

## Market Standing
- **Valuation/Market Cap**: Not disclosed in provided sources
- **Key Metric**: Total Funding $170 million (from respected investors, not all named in sources)
- **Notable Investors/Partners**: Not fully disclosed in provided sources; the $170M raise included "some of the world’s most respected investors"
- **Growth Signals**: Headcount of 200+ spanning 20+ countries; enterprise customers; over 1 billion devices profiled; 8 trillion payments screened; remote-first model enabling global talent acquisition

## Competitive Advantages
- **Unified platform** that combines fraud prevention, AML compliance, identity, and transaction monitoring – replacing dozens of disconnected tools.
- **AI that is transparent and explainable**, designed to augment human judgment, not replace it.
- **Agentic approach** automates repetitive risk operations, freeing analysts for higher-value work.
- **Behavior-infused intelligence** (device, behavioral biometrics) catches fraud early that rule-based systems miss.
- **Sonar consortium network** creates a network effect – the more customers, the stronger the risk intelligence.
- **Focus on financial crime** holistically rather than siloed fraud or compliance.

## Strategic Focus
- Continue building the "agentic risk platform" to automate financial crime operations end-to-end.
- Expand consortium intelligence to provide earlier visibility into mule networks and repeat abusers.
- Deepen partnerships with banks, fintechs, and merchants to embed risk intelligence at every stage of the customer journey.
- Maintain a remote-first, global team to attract top talent across 20+ countries.

## Why Work Here
- **Remote-first culture**: Work from anywhere; team spans 20+ countries.
- **Generous compensation**: Competitive cash and equity grants, with early exercise and extended post-separation exercise window (up to 4 years vs. standard 90 days).
- **Benefits**: 100% health, dental, and vision for employees (60% for dependents), 401(k) with 4% match, flexible PTO (uncapped), year-end break, federal holidays.
- **Perks**: Home office setup (MacBook + stipend), monthly DoorDash/gym/education stipends, meals and fitness allowances.
- **Culture**: Fast-paced, collaborative, grounded in respect for deep work. Emphasis on outcomes, not optics. Team includes operators, engineers, and risk experts who have built systems at scale.
- **Engineering culture**: Strong focus on security, machine learning, and building high-stakes systems; transparent AI meant to empower risk teams.

## Sources
1. [sardine.ai/careers](https://www.sardine.ai/careers)
2. [sardine.ai/about](https://www.sardine.ai/about)
3. [sardine.ai/product](https://www.sardine.ai/)
4. [linkedin.com/company/sardineai](https://www.linkedin.com/company/sardineai)
5. [cbinsights.com/company/sardine](https://www.cbinsights.com/company/sardine)

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