Senior Staff Engineer - Data & ML Ops Platform

Tap Growth ai; Austin (TX); On-site; USD 190,000 - 230,000; Full time

Job summary

Tap Growth ai in Austin, TX is seeking a Senior Staff Engineer to lead our Data & ML Ops Platform initiatives. The role focuses on building scalable data and ML infrastructure, guiding cross-functional teams, and delivering end-to-end pipelines for data and model deployment.

You will partner with stakeholders to shape requirements and raise the bar on reliability and security. The ideal candidate brings 10+ years in data/ML Ops, deep cloud experience across AWS/Azure/GCP, and strong

Qualifications

• 10+ years of experience in data engineering or ML Ops.
• Cloud platform expertise (AWS/Azure/GCP).
• Proficient in Python, Java, or Scala.

Responsibilities

• Architect scalable data and ML Ops solutions.
• Lead cross-functional engineering teams.
• Design end-to-end pipelines for data processing and model deployment.
• Optimize platform performance, reliability, and security.
• Collaborate with stakeholders to define requirements.
• Mentor engineers on best practices and technical excellence.

Skills

Cloud platforms

Python

Java

Scala

Docker

Kubernetes

Leadership

Tools

Docker

Kubernetes

Job description

We're Hiring: Senior Staff Engineer - Data & ML Ops Platform!

We are seeking an experienced Senior Staff Engineer to lead our Data & ML Ops Platform initiatives. The ideal candidate will bring deep technical expertise, leadership skills, and a passion for building robust data and machine learning infrastructure. Join us in shaping the future of intelligent platforms with cutting-edge technology.

Location: Austin, United States
Work Mode: Work from Office
Role: Senior Staff Engineer - Data & ML Ops Platform

What You'll Do:

• Architect scalable data and ML Ops solutions
• Lead cross-functional engineering teams
• Design and implement end-to-end pipelines for data processing and model deployment
• Optimize platform performance, reliability, and security
• Collaborate closely with stakeholders to define requirements
• Mentor engineers on best practices and technical excellence

What We're Looking For:

• Minimum 10 years of experience in data engineering or ML Ops
• Proven expertise in cloud platforms (AWS, Azure, GCP)
• Strong proficiency in Python, Java, or Scala
• Experience with containerization and orchestration tools (Docker, Kubernetes)
• Leadership skills with a track record of driving complex projects
• Excellent communication and collaboration abilities