🛠 Tech Stack

💼 About This Role

You'll build the ML infrastructure foundation for Later's influencer marketing platform. You'll own model experimentation, training, deployment, and monitoring systems to accelerate data science initiatives. This is your chance to define ML Ops standards from the ground up.

🎯 What You'll Do

• Design and build production-grade model deployment and inference systems
• Automate end-to-end ML lifecycle workflows including training and deployment
• Implement monitoring for model performance, drift, and infrastructure health
• Maintain infrastructure-as-code (Terraform, CloudFormation) for cloud environments

📋 Requirements

• 4+ years of experience in ML Ops or ML infrastructure
• Hands-on experience with cloud-native environments (AWS and/or GCP)
• Experience with Amazon SageMaker, Docker, and Flask-based APIs
• Strong programming experience in Python

✨ Nice to Have

• Experience supporting LLMs or generative AI pipelines
• Experience with MLflow, Weights & Biases, or similar tools
• Familiarity with BigQuery and cloud-native data pipelines

🎁 Benefits & Perks

• 🚀 Remote-friendly culture
• 💰 Competitive equity package
• 🏖️ Flexible PTO
• 📈 Professional development budget
• 🧑‍⚕️ Comprehensive health benefits

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min