Senior Software Engineer – Data & ML Platform
Role Overview
Senior Software Engineer role owning production systems and the internal data platform supporting Machine Learning and Operations Research.
Hands-on role spanning backend engineering, cloud infrastructure, and data engineering.
The role has primary ownership and autonomy over systems, architecture, tooling, and engineering practices.
Key Skills for This Role
Full Job Posting
About GoMaterials
GoMaterials operates a B2B marketplace helping landscape contractors source plant and hardscape materials.
The company says it is expanding across North America.
About the role
Senior Software Engineer role owning production systems and the internal data platform supporting Machine Learning and Operations Research.
Hands-on role spanning backend engineering, cloud infrastructure, and data engineering.
The role has primary ownership and autonomy over systems, architecture, tooling, and engineering practices.
Production systems and platform duties
- Own and improve Azure backend services, including serverless services, batch workloads, and ML inference endpoints.
- Manage deployments, reliability, CI/CD, monitoring, alerting, incident response, and operational runbooks.
- Design data pipelines and develop a lakehouse-style analytical layer.
- Maintain infrastructure as code and manage cloud storage, hosting, identity, Key Vault, and costs.
- Implement data monitoring, logging, quality checks, freshness alerts, and secure access controls.
- Build internal services, APIs, and developer tooling as team needs evolve.
ML, engineering, and collaboration
- Provide infrastructure and tooling for ML and operations research experimentation, deployment, evaluation, and reproducibility.
- Productionize research prototypes and own model packaging, versioning, deployment, and CI processes.
- Build automated evaluation and benchmarking pipelines for model performance, drift, and reliability.
- Establish code quality, testing, version control, and CI/CD practices; conduct code reviews.
- Collaborate with Data Science, Operations Research, Product, and Engineering on technical decisions and product integration.
Qualifications available in provided text
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field, or equivalent practical experience.
- Strong programming skills in Python and SQL.
- Strong understanding of APIs, backend service design, and distributed systems.
- Experience building and operating production data pipelines end to end, including retries, idempotency, backfills, orchestration, and freshness monitoring.
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