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skillventory - A Leading Talent Research Firm

Principal Engineer – Python API Development

skillventory - A Leading Talent Research Firm

Principal Engineer on Enterprise AI/ML Platform team tackling complex ML challenges and delivering scalable solutions. Collaborating with multiple teams to build efficient AI/ML capabilities while mentoring engineers.

Posted 7/1/2026full-timeJersey City • New Jersey, Texas • 🇺🇸 United StatesLead💰 $107,000 - $216,000 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureCloudDistributed SystemsGoogle Cloud PlatformGroovyJavaLinuxPythonTerraform

About the role

Key responsibilities & impact
  • Tackle the most complex technical challenges involved in delivering machine learning at enterprise scale
  • Design, build, and evolve reliable, secure, and cost‑efficient platform capabilities
  • Take a hands‑on role across enterprise repositories
  • Improve shared services, CI/CD workflows, and infrastructure patterns
  • Conduct deep technical investigation of performance and scalability issues
  • Analyze system and application metrics
  • Optimize GPU utilization, throughput, and resource efficiency across ML workloads
  • Mentor junior and senior engineers
  • Partner with Data Scientists to package, scale, and operationalize models
  • Lead cross‑platform incident response and post‑mortems

Requirements

What you’ll need
  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a closely related engineering discipline
  • 8+ years (typically 10+) building and operating production platforms and services at scale
  • Deep software engineering expertise in Python and distributed systems
  • A track record of building production‑grade services, libraries, and internal platforms
  • Linux fluency and scripting are required
  • Familiarity with Java or Groovy is a plus
  • Knowledge or experience with GenAI Gateways or LiteLLM a big plus
  • Cloud platform leadership (AWS) —hands‑on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS
  • Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities
  • Exposure to Azure or GCP is beneficial
  • DevOps and CI/CD at scale
  • Infrastructure as Code (CloudFormation, Terraform/OpenTofu)
  • Experience with multi‑environment promotion for ML‑enabled workloads
  • Experience in platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines

Benefits

Comp & perks
  • comprehensive health care coverage and emotional well-being support
  • market-leading retirement
  • generous paid time off and parental leave
  • charitable giving employee match program
  • educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career

ATS Keywords

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Applicant Tracking System Keywords

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

Hard Skills & Tools
Machine LearningDistributed SystemsLinux FluencyScriptingPerformance OptimizationGPU UtilizationProduction-Grade ServicesMulti-Environment PromotionGenAI GatewaysSageMaker
Soft Skills
MentoringCollaboration