Applied AI Research Scientist

Sardine
United States, Canada
Workplace: RemoteFull timeFunction: Data Science & Machine LearningExperience: 4+ yearsSkills: ["Self-management","Communication","Ownership","Growth orientation","Collaboration"]

Apply deep learning and foundation model expertise to Sardine’s fraud and risk datasets, designing experiments and driving research through pretraining, fine-tuning, distillation, quantization, and deployment. Own evaluation and monitoring with offline benchmarks and entity/time-aware holdouts. Partner with Engineering for training infrastructure and production serving, and collaborate with client, Legal, and Compliance teams to translate model capabilities into actionable fraud/AML decisions with governance and documentation.

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FursaFursa
Sardine
Sardine
3 days ago

Applied AI Research Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Apply deep learning and foundation model expertise to Sardine’s fraud and risk datasets, designing experiments and driving research through pretraining, fine-tuning, distillation, quantization, and deployment. Own evaluation and monitoring with offline benchmarks and entity/time-aware holdouts. Partner with Engineering for training infrastructure and production serving, and collaborate with client, Legal, and Compliance teams to translate model capabilities into actionable fraud/AML decisions with governance and documentation.
Location: United States, Canada
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Identify and scope opportunities, design rigorous experiments, and drive the roadmap for foundation model research and development.
  • •Set and maintain evaluation for foundation model performance using offline benchmarks, time-/entity-aware holdouts, calibration, and drift/degradation monitoring.
  • •Take models end-to-end from data prep and tokenization through training, fine-tuning, distillation, quantization, and deployment with tight latency requirements.
  • •Partner with Engineering on training infrastructure, GPU efficiency, feature/embedding stores, and production-scale serving.
  • •Work with client-facing teams and Legal/Compliance/model risk teams to translate model capabilities and limits into actionable decisions with explainability, documentation, and governance.

Pay and Benefits

Perks:Health InsuranceDentalVisionRemote Work401kLearning BudgetHome OfficeMeal StipendWellness StipendPaid Leave

Key Requirements

  • •4+ years in applied machine learning, quantitative modeling, or ML engineering with at least one foundation model pre-trained or substantially adapted and used in real traffic.
  • •Hands-on self-supervised pretraining 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 across data science, engineering, product, marketing, and external partners.
  • •Strong Python and strong SQL, with comfort preparing very large datasets.
Experience:4+ yearsFraudAMLPaymentsCreditAdversarial machine learningLLM-based agentsRegulated financial environment
Skills:Self-managementCommunicationOwnershipGrowth orientationCollaboration
Tech Stack:PythonSQL

Company Brief

Sardine
Provides fraud prevention and account security solutions using machine learning to detect and block account takeover, payment fraud, and malicious actors for digital platforms and marketplaces.
Industry: Cybersecurity
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