The Role

Infrastructure and B2B software companies operate complex systems that process millions of requests per day. When something goes wrong, engineering teams need to quickly understand what changed and why - but the sheer volume of system data they collect makes this incredibly difficult. While they can see individual metrics about API calls, errors, and infrastructure, connecting these signals to find the root cause of issues remains a manual, time-consuming process.

Our ML systems transform how engineering teams understand their systems. Firetiger:

• Detects meaningful changes across different levels of system behavior (customer visible KPIs, application level telemetry, and infrastructure data)
• Clusters and correlates to identify cascading failures and side effects between services
• Applies LLMs to generate clear explanations of complex system state changes
• Predicts potential issues based on historical patterns across multiple data sources

Real example: For a financial firm, our system could correlate infrastructure metrics, API latency patterns, and market data to detect when system behavior is affecting trading outcomes — insights that previously required complex manual analysis across disconnected tools.

You'll work with large-scale data stored in Apache Iceberg tables, applying ML techniques to detect anomalies, identify cause, and generate actionable insights. Our platform runs inside customer cloud infrastructure, giving you access to rich datasets while maintaining data privacy and cost efficiency for our customers.

The Company

Firetiger was founded by **Rustam** and Achille, ex-senior leaders at Cloudflare and Segment. Our product is rooted in operational observability techniques that we developed and applied at Cloudflare and Segment to run mission-critical infrastructure at hyperscale.

We are on a path to do to the Telemetry space what companies like Databricks have done to Business Intelligence. We think that over the next decade, telemetry will be used for a lot more than infrastructure operations, and joining telemetry with other business data will enable customers to extract orders of magnitude more value form it than they have access to today; and we will do this at a fraction of the cost of existing solutions, by leveraging a modern software architecture based on object storage, open data formats, and managed deployments in customers’ cloud infrastructure.

We are backed by Lauren Reeder and Alfred Lin from Sequoia Capital, Matthew Prince (Cloudflare), Calvin French-Owen (Segment), Jean-Denis Greze (Plaid), Jen Taylor (Plaid), and a group of the world’s best investors and operators.

About you

As an ML engineer at Firetiger, you will:

• Design and implement ML models for pattern detection across different types of telemetry data
• Build clustering algorithms to identify related events across system boundaries
• Develop systems to generate human-readable explanations of complex system behavior
• Create prediction models to forecast potential issues based on multi-dimensional data
• Work directly with customers to understand their analysis challenges