Senior Software Engineer, ML Enablement

Etsy

. Build and operate infrastructure for training and serving Etsy's machine learning models .

Posted 9/17/2026full-timeBrooklyn • New York • United StatesSenior💰 $182,000 - $246,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and operating machine learning infrastructure, with strong capabilities in Python programming, cloud technologies, and system design for high-performance model serving. Proficient in optimizing infrastructure for scalability and reliability while collaborating with cross-functional teams.

Highest-signal resume keywords

Python ProgrammingGoogle Cloud PlatformKubernetesMachine Learning FundamentalsSystem Design

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AlgorithmsData StructuresProduction-Ready CodeModel DeploymentPerformance TuningObservability ToolingLLM Serving InfrastructureTransformer ArchitecturesBackend SystemsInfrastructure Troubleshooting

Certifications & Qualifications

Bachelor's Degree in Computer ScienceEquivalent Professional Experience

Industry Keywords

Machine Learning ModelsModel ServingHigh-Availability InfrastructureOpen-Source ModelsSelf-Service Infrastructure

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Build and operate infrastructure for training and serving Etsy's machine learning models
Architect systems for fast, reliable, and scalable model serving at millions of inferences per second
Write high-quality, production-grade Python code and participate in code reviews and pair programming
Help drive architectural decisions and contribute to system design discussions
Build, operate, and improve ML training and serving infrastructure on GCP and Kubernetes
Design and maintain serving infrastructure for open-source and internally hosted LLMs
Manage model deployment and resources and tune performance
Partner with Applied Scientists to translate model training and serving needs into self-service infrastructure
Optimize tradeoffs across performance, cost, and reliability for infrastructure serving 100M+ users
Use generative AI and other productivity tools thoughtfully

Requirements

What you’ll need

Bachelor's degree in Computer Science, Applied Statistics, Mathematics, Electrical Engineering, or a related quantitative field, or equivalent professional experience
5+ years of professional experience building, iterating on, and troubleshooting complex backend and infrastructure systems
Strong software engineering fundamentals, including algorithms and data structures
Production-ready Python coding skills
Hands-on experience with cloud infrastructure, preferably Google Cloud, and Kubernetes
Experience deploying and operating production workloads
Familiarity with observability tooling, including metrics, logging, and tracing
Working knowledge of machine learning fundamentals and concepts
Awareness of LLM serving infrastructure and hosting open-source models
Basic understanding of transformer architectures, predictors, and how model design choices affect serving infrastructure
Comfort with system design for large-scale, high-availability infrastructure

Benefits

Comp & perks

Equity package
Annual performance bonus
Competitive benefits supporting employees and their families
Visa sponsorship may be available for certain roles and skills