Senior ML Platform & Operations Engineer

World; New Germany (MN); On-site; USD 140,000 - 190,000; Full time

Job summary

Tools for Humanity is seeking a Senior ML Platform & Ops Engineer to own the ML lifecycle from data to device across World’s biometric and AI workloads. You will design production‑grade pipelines, ensure telemetry, rollback, and reproducibility, and enable self‑service platforms for researchers and engineers.

You will scale training on multi‑tenant GPU clusters, implement data lineage and security practices, and collaborate with ML research, product, and firmware teams to accelerate reliable ML

Qualifications

• 5+ years building ML infrastructure, data platforms, or production ML systems at scale.
• Track record of delivering platforms and CI/CD pipelines used daily by ML or data teams.
• Hands-on experience running large-scale training on multi-tenant GPU clusters to maximize throughput and reliability.
• Built versioned dataset & lineage systems with provenance and governed access.
• Strong backend skills in Python and/or Go; maintainable code.

Responsibilities

• Design, build, and operate reliable, observable infrastructure for training, evaluation, telemetry ingestion, and deployment.
• Maintain CI/CD workflows and automated pipelines.
• Edge-aware rollout services with staged deployment, A/B experimentation and rollback across devices.
• Develop secure APIs and backend services that expose datasets and model artifacts at scale.
• Implement automated checks, drift detection, and alerting for real-time model monitoring.
• Champion best practices in data lineage, reproducibility, privacy-by-design, security and secure edge delivery.
• Collaborate across ML research, product, and firmware teams to streamline delivery and feedback loops.

Skills

ML infrastructure

CI/CD pipelines

Python/Go

Production systems

Observability

Tools

Docker

Kubernetes/EKS

Terraform/CDK/CloudFormation

Job description

Tools for Humanity is seeking a Senior ML Platform & Ops Engineer to own the ML lifecycle from data to device across World’s biometric and AI workloads. You will design production‑grade pipelines, ensure telemetry, rollback, and reproducibility, and enable self‑service platforms for researchers and engineers.

You will scale training on multi‑tenant GPU clusters, implement data lineage and security practices, and collaborate with ML research, product, and firmware teams to accelerate reliable ML