Applied AI Research Scientist

🔥 16 hours ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sardine

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🔒 Cybersecurity

📋 Compliance

💳 Fintech

Cybersecurity • Compliance • Fintech

Sardine is a cutting-edge platform focused on fraud prevention and compliance. The company offers a behavior-based system for fraud detection, identity verification, and transaction monitoring that helps leading banks, online retailers, and fintechs protect themselves from scams and financial crime. Sardine's technology integrates advanced behavioral biometrics and device intelligence to combat identity fraud, payment fraud, and account takeovers. The platform also streamlines compliance checks such as KYC (Know Your Customer) and AML (Anti-Money Laundering) transaction monitoring. Sardine's comprehensive solution empowers its clients to automate risk decisioning, identify high-risk users early, and manage fraud across the customer journey effectively.

📋 Description

• Identify and scope opportunities, design rigorous experiments, and execute the roadmap for foundation model research and development • Own evaluation of foundation model performance, including offline benchmarks, time- and entity-aware holdouts, calibration, drift and degradation monitoring, and comparisons against classical baselines • Take models from data preparation and tokenization through pretraining, fine-tuning, distillation, quantization, and deployment behind real-time inference paths with tight latency budgets • Partner with Engineering on training infrastructure, GPU efficiency, feature and embedding stores, and production-scale serving • Work with client-facing teams and customers to translate model capabilities and limits into actionable decisions for risk teams • Partner with Legal, Compliance, and customer model risk teams on explainability, documentation, and governance for regulated bank and fintech customers • Scope and drive the next generation of fraud foundation models and industry-wide adoption

🎯 Requirements

• 4+ years in applied machine learning, quantitative modeling, or ML engineering • At least one foundation model pre-trained or substantially adapted and put in front of real traffic • Hands-on self-supervised pre-training experience • Practical fine-tuning and adaptation experience • Production experience with model serving, versioning, monitoring, and rollback • Ability to self-manage and drive ambiguous applied research projects • Clear communication with partner teams across data science, engineering, product, marketing, and external partners • Strong Python • Strong SQL • Comfort preparing very large datasets • Background in fraud, AML, payments, credit, or adversarial machine learning is a plus • Experience building and evaluating LLM-based agents in production is a plus • Publications, released models, or open-source contributions in representation learning or sequence modeling are a plus • Experience with model risk management and documentation in a regulated financial environment is a plus

🏖️ Benefits

• 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