🛠 Tech Stack

💼 About This Role

You'll design, build, and maintain scalable MLOps pipelines supporting the full machine learning lifecycle. You'll optimize CI/CD pipelines for ML workflows and ensure data systems are reliable, secure, and efficient. This role offers a remote-first environment with high flexibility and autonomy.

🎯 What You'll Do

• Design and maintain scalable MLOps pipelines for ML lifecycle
• Optimize CI/CD pipelines for machine learning workflows
• Implement monitoring and observability for production ML models
• Ensure data security, governance, and compliance in production systems

📋 Requirements

• Strong experience in MLOps including automation and lifecycle management
• Advanced knowledge of Docker and Kubernetes
• Solid experience with AWS for data and ML workloads
• Proficiency in Python for data engineering and automation

✨ Nice to Have

• Familiarity with MLflow, Kubeflow, or SageMaker Pipelines
• Knowledge of Terraform or CloudFormation
• Experience with generative AI projects

🎁 Benefits & Perks

• 🏖️ Fully remote work with high flexibility and autonomy
• 🩺 Health and dental insurance plans
• 🧘 Wellness benefits including fitness partnerships and programs
• 📚 Education support and career development programs
• 👶 Extended maternity and paternity leave

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min