Senior ML Ops Engineer — Remote • Unlimited PTO

Nift; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Flexible remote work

Unlimited PTO

Job summary

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We’re seeking a hands-on ML Ops Engineer to partner with data scientists and turn models into production systems. You’ll architect storage/compute, harden pipelines, and ensure reliability and cost-efficiency.

Reporting to the Data Science Manager, you’ll lead CI/CD, model governance, feature store concepts, and cross-functional collaboration to scale our ML platform across the organization.

Qualifications

• 5+ years in ML Ops with ownership of large-scale ML infra.
• Strong Python coding, debugging, testing, and CI/CD discipline.
• Experience with AWS and containerized environments.
• Experience with ML tooling and model governance.
• Excellent collaboration with data scientists and engineers.
• Experience with large-scale batch/stream processing (PySpark/Kafka).

Responsibilities

• ML platform: Productionize training and inference (batch/real-time), establish CI/CD for models and data/versioning practices.
• Feature & model lifecycle: Centralize feature generation and manage model registry/metadata.
• Observability & quality: Implement monitoring for data quality, drift, model performance/latency, and pipeline health.
• Engineering excellence: Refactor research code into reusable components, ensure repo structure and testing.
• Cross-functional collaboration: Work with DS/Analytics/Engineers to turn prototypes into production systems, provide mentorship.
• Roadmap & standards: Drive technical vision for ML platform capabilities and set architectural patterns.

Skills

ML Ops

Python

CI/CD

AWS

Docker

Kubernetes

Terraform

Databricks

SageMaker

MLflow

Feature stores

Model governance

PySpark

Kafka

Data versioning

Collaboration

Tools

Databricks

SageMaker

Git

Airflow

Job description

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We’re seeking a hands-on ML Ops Engineer to partner with data scientists and turn models into production systems. You’ll architect storage/compute, harden pipelines, and ensure reliability and cost-efficiency.

Reporting to the Data Science Manager, you’ll lead CI/CD, model governance, feature store concepts, and cross-functional collaboration to scale our ML platform across the organization.