BlueHarbor Decision Intelligence is hiring a Senior Offre d'emploi full remote USA — ML Engineer on the ML platform team (Remote · New York, 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.
BlueHarbor Decision Intelligence cherche un ML Engineer pour industrialiser modeles de scoring et pipelines de monitoring en production.
Full remote USA avec recouvrement Europe possible pour profils seniors.
BlueHarbor Decision Intelligence needs someone who can move training, deployment, observability, and cost control from experiment to production—with tests, monitoring, and stakeholder-ready communication.
The ML platform group partners closely with product and domain experts; you will translate ambiguous requirements into measurable ML or LLM outcomes.
What you will do
- Design and ship training, deployment, observability, and cost control with offline evals, dashboards, and rollback plans.
- Improve datasets, labeling, and metrics that correlate with user or business outcomes.
- Review model changes for safety, bias, latency, and infrastructure cost before wide release.
- Document decisions so on-call, support, and compliance teams can act without guesswork.
- Collaborate async with written specs, demos, and recorded design reviews.
What we look for
- Demonstrated production use of core skills such as Python, PyTorch, SQL, AWS—with repos, writeups, or metrics we can verify.
- Comfort operating the listed toolchain (Docker, Kubernetes) in real environments—not tutorials only.
- Ownership of at least one feature or model from design through post-launch review—including failure modes you handled.
- Clear communication on trade-offs (quality, cost, latency, safety) with product and non-technical stakeholders.
- Eligible to work in United States (or remote policy as stated in the listing).
Benefits & ways of working
- Health plan, equipment budget, annual retreat.
