Forward Deployed ML/AI Engineer

📋 Description

• End-to-end lifecycle of intelligent systems: data ingest, train, deploy.
• Design scalable APIs; optimize inference latency; architect full-stack infra.
• Work with classical ML models and Generative AI (LLMs, RAG, agents).
• Translate AI research to production and business impact.
• Own end-to-end delivery and guide executive stakeholders.
• Collaborate with customer teams to align with business OKRs.

🎯 Requirements

• 6+ years of ML, SWE GenAI, or DS with productionized models.
• 3+ years of implementation and customer-facing experience.
• Classical ML and GenAI: scikit-learn, XGBoost; LLMs, RAG, vector DBs.
• Full-stack: Python, FastAPI/Flask, Streamlit.
• MLOps: Docker and CI/CD pipelines for prod deployment.
• Cloud infra and data engineering basics: AWS/GCP/Azure; SQL/NoSQL.

🎁 Benefits

• Equity ownership.
• Annual company retreat.
• Education bonus for continuous learning.
• Winter company break.
• Paid time off.
• Tailored career roadmaps.