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Senior MLOps Engineer
Nadia Kowalski
Full-time · Senior · New_York
About the role
I want to be honest with you about what we are and what we're not. We are a 400-person company. We have a mature product, a real revenue base, and a data science team that has been shipping models for four years. We are not a startup. We do not move fast. We have compliance requirements, change management processes, and an infosec review that adds two weeks to any third-party integration. If you want to feel like a hero who single-handedly transforms a company in ninety days, this is probably not the right place for you. What we do have is a genuinely hard infrastructure problem that has been partially solved, badly, by three different teams over three years, and a leadership team that is finally serious about fixing it properly. We want someone experienced enough to diagnose what's actually wrong — not just what looks wrong — and patient enough to fix it in an organisation that moves at enterprise speed. If you've spent time inside a company like ours and understand why change is hard before you understand why it's necessary, please apply. That context is the most valuable thing you could bring.
Responsibilities
- Produce a written architecture review of the current ML platform: gaps, risks, and a prioritised remediation plan
- Lead the migration of model serving from our current ad-hoc ECS deployment to a standardised Kubernetes-based platform
- Build automated retraining and deployment pipelines for our eight highest-priority production models
- Define observability standards for model serving: latency SLOs, prediction monitoring, and alerting
- Work across data science, platform, and infosec teams to drive technical decisions through proper approval processes
Requirements
- 6+ years in data engineering, platform engineering, or MLOps with at least three years at a company of 200+ employees
- Kubernetes at production depth — cluster administration, resource governance, multi-tenant namespace design
- MLflow or an equivalent model registry and experiment tracking system in a real production setting
- AWS including EKS, S3, IAM boundary policies, and VPC design — you've navigated enterprise AWS, not just sandbox accounts
- Terraform with cross-team module sharing and state management at scale
- Experience working within change management and infosec review processes without circumventing them
Benefits
- Stable, funded company with real engineering problems — no runway anxiety
- Full remote with quarterly in-person team meetings (travel covered)
- $130,000 – $155,000 base salary + annual bonus
- $2,000 annual learning budget
- Generous pension contribution — 6% employer match
Job Type
Full-time
Level
Senior
Language
English
Salary Range
$130,000 – $155,000
AI Expertise
MLOps & AI Infrastructure
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