Tech Lead – MLOps, Infrastructure

🔥 17 hours ago

🇺🇸 United States – Remote

💵 $80 - $120 / hour

⏳ Contract/Temporary

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 6%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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MegazoneCloud US

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • Enterprise

MegazoneCloud US is a cloud-native AI and digital transformation services provider that helps organizations become AI-native through cloud migration, generative AI, data & AI platforms, and integrated security solutions. The company partners with major technology vendors (notably AWS and NVIDIA) and offers enterprise-focused products and services such as AI contact centers, AI SDLC consulting, cloud modernization, managed cloud services, and industry-specialized AI models to accelerate secure, scalable AI-driven operations. MegazoneCloud also emphasizes governance, compliance, and hybrid enterprise solutions while expanding its global footprint, particularly in the U. S.

📋 Description

• Own the design and implementation of production-grade ML pipelines • Lead architecture and implementation of end-to-end MLOps pipelines, including CI/CD for training, evaluation, approval, and deployment with audit trails • Design and deploy Terraform infrastructure for ML platform resources • Build automated Amazon SageMaker training jobs for life sciences workloads • Implement model performance monitoring and automated retraining triggers • Establish CI/CD for ML artifacts, including versioning, container builds, integration testing, and staged rollouts with validation gates • Design model registries and artifact management for governance, reproducibility, and 21 CFR Part 11 compliance • Implement monitoring, alerting, and auto-scaling for training and inference workloads • Define and enforce MLOps best practices, coding standards, and architectural patterns • Serve as overall Tech Lead through architecture reviews, mentoring, and technical decision-making • Coordinate with customer platform, IT security, and quality teams on networking, security, and compliance

🎯 Requirements

• Technical leadership experience in MLOps and infrastructure • Experience designing and implementing production-grade ML pipelines • Experience with infrastructure-as-code using Terraform • Experience building automated training jobs on Amazon SageMaker • Knowledge of hyperparameter tuning, distributed training, and spot optimization • Experience implementing model performance monitoring, data drift detection, prediction quality tracking, and automated retraining triggers • Experience with CI/CD for ML artifacts, model versioning, container builds, integration testing, and staged rollouts • Knowledge of model registries and artifact management for governance and reproducibility • Knowledge of 21 CFR Part 11 compliance • Experience with infrastructure monitoring, alerting, and auto-scaling • Ability to define and enforce MLOps best practices, coding standards, and architectural patterns • Ability to conduct architecture reviews, mentor, and make technical decisions • Ability to coordinate with platform, IT security, and quality teams • Must be eligible to work in the United States for any employer • Must not require employment visa sponsorship

🏖️ Benefits

• Growth and professional development investment • Servant leadership and management support • Flat organization with direct impact on technical roadmap and client success • Learn-from-it culture treating mistakes as learning opportunities • Equal employment opportunity employer