Cascadia Inference Co is hiring a Senior Senior ML Platform Engineer on the ML platform team (Hybrid · Seattle, United States). This is a hands-on role in ML platform & MLOps—not a generic “AI enthusiast” post.
You will own training, deployment, observability, and cost control end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
Cascadia Inference Co powers batch and realtime ML for SaaS analytics products used by Fortune 500 teams. Our platform blends Spark/Ray workloads with GPU bursts and humane FinOps dashboards.
Hiring a Senior ML Platform Engineer in Seattle (hybrid) to deepen training orchestration and feature freshness guarantees.
What you will do
- Evolve orchestration for large-scale offline training jobs with preemptible fleets and checkpointing discipline.
- Improve feature store ingestion SLAs and backfill ergonomics for data scientists.
- Instrument cost attribution by team, workload, and model version; drive optimisation programs.
- Collaborate with SRE on incident tooling for ML pipelines distinct from classical services.
- Prototype next-gen tooling (workflow engines, policy-as-code for compute quotas).
What we look for
- 5+ years building ML or data platforms in cloud-native environments.
- Strong Python and Kubernetes; comfort with Spark or Ray operational concerns.
- Systems thinking and measured rollouts; customer empathy for DS personas.
- US work authorisation.
Nice to have
- Experience with GPU schedulers (Volcano, Run:ai) or Slurm bridges.
- Prior FinOps or unit economics modelling for infra teams.