Sr ML Engineer, Admin Central
Core
Building mission-critical distributed systems, high-availability usage pipelines, and agentic AI functionality to unify the admin experience and power enterprise billing integrity at scale.
Role type
Senior IC Machine Learning Infrastructure Engineer (Agentic AI & LLMs)
Builds
Distributed ML pipelines, agentic workflows, real-time inference microservices, and feature stores for global product regions.
Domain
Enterprise SaaS / AI Platform / Distributed Systems
Deliverable
production ML models
Required skills
Distributed data processing (Spark, Flink, Kafka), LLM orchestration (LangChain, LlamaIndex), Deep Learning (PyTorch, TensorFlow), High-performance backend (Java, Go, Scala, C++), MLOps (Kubeflow, MLflow, Airflow), Vector databases (Pinecone, Milvus), Cloud-native deployment (Docker, Kubernetes, gRPC/REST)
Preferred skills
RAG architectures, LLM fine-tuning, Model-Based Design, Multi-agent orchestration, Feature engineering for vector embeddings
Technologies
PyTorch, TensorFlow, LangChain, LlamaIndex, Spark, Flink, Kafka, ClickHouse, Apache Iceberg, OpenTelemetry, LangSmith, Kubeflow, MLflow, Airflow, SageMaker, Docker, Kubernetes, gRPC, REST
Responsibilities
Architect and deploy end-to-end ML pipelines from data ingestion to production; Design LLM-driven recommendation features and agentic workflows; Optimize real-time model inference for sub-second latency; Integrate telemetry and tracing for model observability; Collaborate on big data platforms for feature retrieval; Partner with cross-functional teams to translate business requirements into scalable ML solutions.
Seniority
Senior, hands-on IC
