V
Lead Software Engineer – Innovation Team
On-siteFull-timeFull-stack DevelopmentEnterprise Software
Join a fast-moving product team building systems that convert machine-learning predictions into automated customer decisions. You will work across cloud data pipelines, ML and decisioning services, backend applications, and user interfaces, taking features from architecture through production and —d
Responsibilities
- Design and build production-grade systems across cloud data pipelines, ML and decisioning services, backend applications, and customer-facing UI.
- Turn machine-learning predictions into automated decisions delivered to customer databases and CRM systems, and feed outcomes back into the learning loop.
- Own features from architecture and implementation through deployment, monitoring, and iteration.
- Collaborate with engineering, product, and data science leaders to productionize research and models at scale.
- Monitor system performance and prioritize work using data-driven decisions.
- Participate in code reviews and maintain engineering standards and best practices.
Requirements
- At least 5 years of hands-on experience building and operating large-scale production cloud systems end to end.
- Strong software engineering fundamentals, including software design, concurrency, data structures, and cost-performance trade-offs.
- Experience with cloud-native, event-driven architectures such as AWS Lambda, SQS, S3, or equivalent services.
- Experience with modern data warehouses and pipeline tooling, such as Snowflake, BigQuery, Databricks, dbt, Airflow, Spark, or Glue.
- Proficiency in Python or a comparable general-purpose language, with the ability to learn Python quickly.
- Willingness to work across data pipelines, backend services, machine-learning code, and frontend applications.
- Bachelor’s degree in Computer Science, Engineering, or an equivalent qualification.
- Strong ownership, communication, independent-learning, and problem-solving skills.
Nice to have
- Experience with applied machine learning or experimentation systems, including recommendation, ranking, bandits, A/B testing, or causal inference.
- Frontend or UI experience, including dashboards and configuration tools.
- Experience with Docker, Kubernetes, or ArgoCD.
- Experience with infrastructure as code using Pulumi or Terraform.
- An MSc in Computer Science or Engineering.