Stord is building ML capabilities that directly power our cloud-based supply chain platform, handling over $10B in commerce annually. As a Senior Machine Learning Engineer, you'll own the full ML lifecycle—from model design and training through production deployment and improvement. This is a high-impact, hands-on role where your work will directly influence how millions of shipments are planned, routed, and fulfilled.
What You'll Do
- Design, train, and evaluate ML models for logistics use cases: delivery time estimation, demand forecasting, capacity planning, and anomaly detection.
- Improve and iterate on existing production models using performance data and customer feedback.
- Run structured experiments to validate model improvements before promotion to production.
- Define evaluation frameworks and success metrics in collaboration with the Data Scientist and product teams.
- Own the full path from trained model to production API—wrapping, deploying, versioning, and monitoring.
- Build and maintain inference APIs serving predictions at scale with <100ms latency targets.
- Deploy and manage models on GCP Vertex AI.
- Implement A/B testing and rollback strategies for safe model promotion.
- Build real-time and batch feature pipelines from Postgres/AlloyDB sources.
- Design feature stores serving both training and inference.
- Implement data validation and quality monitoring to catch drift before it affects customers.
- Develop CI/CD pipelines for model deployment.
- Monitor model and pipeline health; own incident response for ML systems.
- Optimize inference costs across GCP and Cloudflare infrastructure.
- Partner with the Data Scientist on experiment design and feature strategy.
- Work with platform engineers to integrate ML outputs into core product services.
- Communicate model behavior, limitations, and tradeoffs clearly to non-ML engineers and product stakeholders.
What We're Looking For
- 4+ years of ML engineering experience, with models shipped to production.
- Strong Python—training pipelines, model evaluation, production code (not just notebooks).
- Experience with cloud ML platforms, preferably GCP Vertex AI.
- Data engineering fundamentals: ETL/ELT, streaming data, SQL at scale.
- TypeScript or Elixir experience, or demonstrated ability to build APIs in unfamiliar languages.
- Familiarity with logistics, e-commerce, fulfillment, or supply chain domains—you understand operational concepts like on-time delivery, carrier selection, and warehouse throughput.
Nice to Have
- Kafka or streaming pipeline experience.
- Feature store experience (Feast, Tecton, or equivalent).
- Hands-on with Kubernetes or container orchestration.
- Cloudflare Workers or edge inference experience.
- Experience improving existing production models, not just building greenfield.
Technical Stack
- Python, GCP Vertex AI, Postgres, AlloyDB, SQL, TypeScript, Elixir, Kafka, Feast, Tecton, Kubernetes, Cloudflare Workers
Team & Environment
You'll work alongside a Senior Data Scientist as part of a small, ambitious team with direct visibility into customer impact. Stord is a rapidly growing company with an energetic, expert culture.
