🛠 Tech Stack

💼 About This Role

You'll build and maintain ML training, inference, and serving pipelines for Kargo's ad platform, directly impacting auction optimization, outcome prediction, and content recommendations. You'll take models from data science prototypes into production, moving revenue metrics at programmatic scale.

🎯 What You'll Do

• Own deployment of 2-3 ML models into production (batch or real-time)
• Reduce model serving incidents and latency regressions
• Deliver improvements to shared ML infrastructure (CI/CD, feature pipelines)
• Partner with Data Science and Product to productionize revenue-impacting models

📋 Requirements

• 2-4 years building and deploying ML systems in production
• Strong Python with ML frameworks (PyTorch, TensorFlow)
• Experience with AWS ML services (SageMaker, EC2, Lambda)
• Proficiency with large-scale data tooling — SQL, Spark, Snowflake

✨ Nice to Have

• Experience with model serving frameworks (Triton, FastAPI)
• Containerization (Docker, Kubernetes) or IaC tooling
• AdTech, real-time bidding, or LLMs/embeddings exposure

🎁 Benefits & Perks

• 💰 Competitive salary with $90k-$110k base range
• 🏖️ Hybrid work with 4 days onsite in NYC
• 🏆 Award-winning culture (AdAge Best Places to Work, Built In Best Places to Work)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Phone Screen· 45 min
3. 3Onsite Interviews (4-5 rounds)· 4-5 hours