Software Engineer — ML Platform
Location: Remote / Hybrid
We’re looking for a Software Engineer to build and scale the systems powering our advertising and data workflows.
We work with large-scale advertising and attribution datasets, building systems that connect audience intelligence with campaign execution and measurement.
This role sits across backend engineering, data engineering, and ML/data infrastructure. You’ll work across APIs, event pipelines, data infrastructure, partner integrations, and internal tooling supporting campaign workflows and ML/data systems.
The role is best suited for engineers who enjoy operating across systems rather than staying within a single specialization.
What You’ll Work On
Backend & Platform Engineering
- Build and maintain backend services, APIs, and internal tooling
- Design asynchronous workflows and distributed processing systems
- Improve observability, reliability, and deployment workflows
- Debug production issues across infrastructure, application, and data layers
Data Engineering
- Build and maintain scalable ingestion and processing pipelines
- Process high-volume event and attribution datasets across operational systems
- Design reliable data workflows and maintainable data models
ML Infrastructure & Experimentation
- Support ML systems with reliable training and inference datasets
- Build pipelines supporting experimentation and feature generation
- Collaborate with ML engineers on production integrations and evaluation workflows
Partner Data & Integrations
- Integrate external APIs, partner platforms, and operational systems
- Build resilient ingestion systems handling retries, quotas, pagination, and evolving schemas
- Support privacy-conscious attribution and partner data workflows
Tech Stack
Core Technologies
- Python
- SQL
- PostgreSQL
- Snowflake
Infrastructure & Platform
- GCP or AWS
- CI/CD pipelines
- Infrastructure as code
Nice to Have
- dbt
- FastAPI or similar backend frameworks
- Kafka, Pub/Sub, or streaming systems
- AdTech, MarTech, or travel-tech systems
- ML data or experimentation systems
What We’re Looking For
- 3–5 years of experience in software engineering, data engineering, or platform engineering
- Strong programming skills, especially in Python
- Solid SQL and data modeling fundamentals
- Experience building production systems in cloud environments
- Understanding of distributed systems, asynchronous workflows, and operational reliability
- Strong ownership mindset and ability to drive work independently
- Strong engineering fundamentals and ability to quickly learn unfamiliar systems, tools, and domains
Nice-to-Have Experience
- High-volume event or analytics systems
- Advertising, attribution, or customer data platforms
- ML data pipelines or experimentation systems
- API-heavy integration platforms
- Comfortable using AI-assisted engineering tools such as Claude Code, Gemini CLI, OpenAI Codex, GitHub Copilot, or similar developer agents as part of day-to-day development workflows
Why Join
- Work on challenging distributed systems and large-scale data workflows
- Build modern platform and data infrastructure with real business impact
- High ownership and opportunity to grow across multiple engineering domains
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