Senior Data/ML Engineer (Fintech)

Location: Remote within the United States or Canada; candidates must keep a home base in the country where they are hired.

Salary: US$150,000–$205,000 for the United States or CA$170,000–CA$255,000 for Canada, plus equity.

Company

Sardine provides an agentic risk platform that unifies fraud, identity, compliance, and AML data to help organizations prevent financial crime and AI-driven attacks.

What you will do

• Own streaming and batch data ingestion pipelines for device telemetry, transactions, KYC signals, and third-party enrichment.
• Build and evolve the feature platform using Flink, Spark, Chronon, and low-latency feature serving.
• Productionize fraud and identity ML models, including training, explainability, automated retraining, champion/challenger promotion, and rollback.
• Develop KYC, AML, sanctions, identity, entity-resolution, and graph-based risk signals across multiple data sources.
• Own BigQuery warehouse modeling, training datasets, data-source integrations, failover, caching, and cost controls.
• Set technical direction through design reviews, mentoring, architecture decisions, and build-versus-buy evaluations.

Requirements

• 8+ years of experience building production data and machine learning systems with ownership of both pipelines and models.
• Deep Python and strong SQL skills, plus expertise with Spark, Beam, or Flink and streaming semantics.
• Experience with GCP data and ML services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Composer, and Vertex AI, or equivalent AWS services.
• Experience with feature stores, training-serving parity, gradient-boosted models, rare-event modeling, monitoring, drift detection, and explainability.
• Experience with high-volume, low-latency serving and regulated-domain data governance, including PII, encryption, access control, residency, and auditability.
• Experience in fraud, risk, payments, lending, or identity/KYC, or the ability to quickly develop expertise in a regulated domain.

Nice to have

• Experience with customer-facing ML, bring-your-own-model integrations, adverse-action explainability, or shadow and challenger scoring.
• Experience in high-growth B2B SaaS or as an early data/ML hire.

Culture & Benefits

• Remote-first work environment with flexible working practices focused on results rather than hours.
• Flexible paid time off and a year-end break.
• Health, dental, and vision coverage for employees and dependents.
• 401(k) or RRSP matching, a MacBook Pro, and a home-office setup stipend.
• Meal, social meet-up, health and wellness, and annual learning stipends.
• Cash compensation plus equity, including early exercise for options.