Staff Engineer - DS/ML

We are looking for a Senior or Staff Backend Engineer with deep experience in data-intensive systems, modern data pipelines, and backend services that operate at scale.

You will design and build critical components of our Data Platform, enabling structured ingestion, transformation, real-time and batch processing, and integration with AI workflows. This role combines system design, backend engineering, and platform thinking—with the opportunity to influence core architectural direction.

You’ll work closely with product managers, data scientists, infra and application engineers to ensure our data platform is reliable, scalable, and AI-ready.

• Architect Multi-Tenant Data Infrastructure - Build data systems with strong tenant isolation guarantees, while supporting tenant-specific configuration, schema extensions, and custom data ingestion pipelines.
  
• Enable Probabilistic and Attribution-Driven Models - Lay the backend foundations for models that operate on probabilistic reasoning, sequence attribution, and temporal causality. Partner with data scientists to expose necessary event logs, intermediate representations, and counterfactual support for explainable outcomes.
  
• Ensure data integrity, lineage, and auditability across tenants with dynamic configuration needs.
  
• Design, build, and maintain scalable backend services that support data ingestion, data pipelines, metadata management, and the data warehouse
  
• Work across streaming and batch paradigms, building frameworks that support high-velocity real-time events as well as durable historical datasets
  
• Collaborate on the architecture of our next-generation data platform—balancing flexibility, performance, and cost
  
• Implement observability, SLAs, and fault tolerance across critical data flows
  
• Partner with ML and analytics teams to enable data products such as behavioral modeling, conversation intelligence, and user analytics
  
• Build and maintain APIs, microservices, and orchestration systems that expose data pipelines as first-class infrastructure
  
• Drive technical excellence through design reviews, code quality, documentation, and mentorship

• Scalable ingestion systems that support structured, semi-structured, and event-based data
  
• A unified data layer powering internal analytics and external-facing dashboards
  
• Backend systems that are robust, monitored, and support low-latency query and job execution
  
• Data infrastructure that is modular, reusable, and developer-friendly across use cases
  
• Increased data reliability, accuracy, and freshness across mission-critical services

• 6+ years of backend engineering experience with a focus on data-intensive applications
  
• Experience designing backend systems in multi-tenant, configuration-rich environments.
  
• A high attention to detail and craftsmanship around data correctness, versioning, and recovery.
  
• Strong command of backend development using languages such as Python, Go, or Java
  
• Experience with building distributed systems, streaming (Kafka, Pulsar, etc.), or batch orchestration (Airflow, Dagster, dbt)
  
• Strong knowledge of modern data architecture principles, including data lakes, lakehouses, or warehouse-first designs
  
• Experience working with cloud-native data warehouses (e.g., Snowflake, BigQuery, Redshift) and storage systems (e.g., S3, GCS)
  
• Understanding of schema management, versioning, metadata systems, and data governance
  
• Familiarity with performance tuning, concurrency, and reliability in backend services
  
• Comfort working with stochastic and causal reasoning frameworks, and the system-level implications for such modeling (e.g., replay, feature provenance, sequence entropy).

• Prior work on platform or infrastructure teams supporting ML, analytics, or product instrumentation
  
• Exposure to personalization infrastructure, including behavioral embeddings, identity resolution, and per-user vector stores or feature stores.
  
• Exposure to data mesh, domain-driven data modeling, or federated governance models
  
• Experience with statistical debugging, attribution analysis, or systems that operate under uncertainty or partial observability
  
• Experience integrating security, compliance, and auditability into data platform components Why Join Us
  • Work on critical infrastructure at the heart of AI-first products in financial services
    
  • Solve real-world challenges in scale, latency, observability, and developer ergonomics
    
  • Collaborate with an exceptional team of engineers, data scientists, and product leaders
    
  • Shape the architecture of a modern platform powering AI agents and real-time intelligence

The base salary range for this role will be between $225,000 to $260,000. Final compensation will be determined by a variety of factors, including, but not limited to your location, skills, experience, education, and/or professional certifications. During the phone screening, your recruiter will provide the location-specific salary range for this role. Regardless of your personal situation or where you are in the world, Interface.ai offers comprehensive and great benefits programs to meet your needs:

• Health: medical, dental, and vision insurance and wellbeing resources and programs
• Time away: Public holidays and discretionary PTO package for flexible days off with manager approval
• Financial: 401K, ESPP, Basic life and AD&D insurance, long-term and short-term disability
• Family: parental leave, maternity support, fertility services
• Development: Access to internal professional development resources.
• Additional: 24/7 access to professional counselors, voluntary insurance coverage, exclusive perks and discounts