Staff Platform Machine Learning Engineer – Engine

Jobtailor; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced platform/DevOps engineer to design and maintain infrastructure for ML training, deployment, and inference. You will own CI/CD, IaC, observability, and operational tooling to support reliable, scalable ML workloads.

Responsibilities include operating distributed systems in production, building Kubernetes- and cloud-based services, and collaborating with data scientists and engineers to optimize model deployment and data workflows.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 7+ years of experience in software engineering, platform engineering, or DevOps/SRE roles.
• Strong systems engineering background with production operations experience.
• Hands-on experience with cloud infrastructure and tooling (AWS, Docker, Kubernetes, Terraform, CI/CD, monitoring).
• Experience operating distributed systems in production.
• Experience with ML infrastructure, model serving, or data platforms is a strong plus.

Responsibilities

• Design, build, and maintain infrastructure supporting ML training, deployment, and inference workloads.
• Own and improve CI/CD, infrastructure-as-code, observability, and operational tooling for ML systems.
• Operate and evolve production systems with a strong focus on reliability, performance, and cost efficiency.
• Build and maintain Kubernetes- and cloud-based services that support model execution and data workflows.
• Partner with data scientists and engineers to support model deployment and operational needs.
• Improve developer workflows through automation, tooling, and platform abstractions.
• Participate in on-call and operational ownership for platform components.

Skills

Problem-Solving

Operations-First Mindset

Adaptability

Team Collaboration

Education

Bachelor’s Degree

Master’s Degree

Tools

AWS

Docker

Kubernetes

Terraform

CI/CD

Monitoring

Observability

Infrastructure-as-Code

Automation

Cloud Infrastructure

Job description

• Design, build, and maintain infrastructure supporting ML training, deployment, and inference workloads.
• Own and improve CI/CD, infrastructure-as-code, observability, and operational tooling for ML systems.
• Operate and evolve production systems with a strong focus on reliability, performance, and cost efficiency.
• Build and maintain Kubernetes- and cloud-based services that support model execution and data workflows.
• Partner with data scientists and engineers to support model deployment and operational needs.
• Improve developer workflows through automation, tooling, and platform abstractions.
• Participate in on-call and operational ownership for platform components.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 7+ years of experience in software engineering, platform engineering, or DevOps/SRE roles
• Strong systems engineering background with production operations experience
• Strong experience with backend or platform services
• Hands‑on experience with cloud infrastructure and tooling (e.g., AWS, Docker, Kubernetes, Terraform, CI/CD, monitoring)
• Experience operating distributed systems in production
• Experience with machine learning infrastructure, model serving, or data platforms is a strong plus
• Strong problem‑solving skills and an operations‑first mindset
• Ability to thrive in a fast‑paced, high‑tech environment and manage complex problems

Core Competencies

Demonstrates expertise in designing and maintaining infrastructure for machine learning workloads, with a strong focus on reliability, performance, and cost efficiency. Proficient in cloud infrastructure, CI/CD, and operational tooling to enhance developer workflows and support model deployment.

Highest-signal resume keywords

• Cloud Infrastructure
• Kubernetes
• CI/CD
• Machine Learning Infrastructure
• Systems Engineering

ATS Optimization Keywords

Hard Skills

• Software Engineering
• Platform Engineering
• DevOps
• Backend Services
• Production Operations
• Distributed Systems
• Model Serving
• Data Platforms
• Infrastructure-as-Code
• Automation

Soft Skills

• Problem‑Solving
• Operations-First Mindset
• Adaptability

Certifications & Qualifications

• Bachelor’s Degree
• Master’s Degree

Industry Keywords

• Machine Learning
• Observability
• Operational Tooling
• Data Workflows

Tools & Technologies

• AWS
• Docker
• Terraform
• Monitoring Tools