Senior ML Engineer, Production ML & MLOps

Attain; Redwood City (CA); Hybrid; USD 170,000 - 260,000; Full time

Benefits offered by this job

Hybrid schedule

Job summary

Attain is seeking a Senior/Staff Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our fintech suite. This role is highly hands-on and focuses on pipelines, feature infrastructure, model-serving, CI/CD, and observability across our app portfolio.

You will work on creating reliable, scalable ML platforms, streamlining retraining and rollouts, and ensuring performance, security, and cost-efficiency in production.

Qualifications

• 5+ years of direct experience building and operating production ML systems.
• Strong software and platform engineering fundamentals.
• Experience with model deployment, monitoring, and retraining in production.
• Hands-on MLOps with pipelines, Docker, Kubernetes, Terraform, and CI/CD.

Responsibilities

• Build, deploy, and operate production ML systems at the core of our platform.
• Develop and improve feature pipelines, model-serving, and CI/CD workflows.
• Monitor, retrain, and roll out models with safe, scalable processes.
• Collaborate with data scientists, engineers, and product teams to deliver reliable ML solutions.
• Instrument systems with observability and alerting to ensure performance and cost efficiency.

Skills

Machine Learning

MLOps

CI/CD

Kubernetes

Terraform

Python

Go or Rust

SQL

BigQuery

Distributed compute

Education

BS in CS or related

Tools

Docker

Prometheus

Grafana

Airflow

CI/CD tooling

Job description

Attain is seeking a Senior/Staff Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our fintech suite. This role is highly hands-on and focuses on pipelines, feature infrastructure, model-serving, CI/CD, and observability across our app portfolio.

You will work on creating reliable, scalable ML platforms, streamlining retraining and rollouts, and ensuring performance, security, and cost-efficiency in production.