Senior AI Machine Learning Engineer

Requirements

• - 3+ years of hands-on ML/AI engineering with demonstrated end-to-end system ownership
• - Production experience building LLM-powered applications (not just API consumption)
• - Hands-on experience with agent orchestration: LangGraph, CrewAI, or AutoGen in production
• - Production RAG experience with evaluation metrics, hybrid search, and re-ranking strategies
• - Experience building ML models: churn, propensity, LTV, segmentation, recommendation systems
• - Hands-on experience with data pipelines: Spark for batch, Flink or Kafka Streams for real-time
• - Strong Python proficiency: production code structure, async, multiprocessing, profiling, optimization
• - Experience with vector databases at scale: OpenSearch k-NN, Qdrant, or Milvus
• - Production MLOps experience: MLflow, experiment tracking, model registry, drift monitoring
• - Real-time ML inference experience at 1,000+ QPS
• Good to Have:
• - Experience at AI-first companies or building AI/ML platforms from scratch
• - Telco or enterprise data platform background
• - Experience with LLM fine-tuning: LoRA, QLoRA, PEFT techniques
• - Experience with embedding models: sentence-transformers, fine-tuning for domain
• - Kubernetes for ML workload orchestration and GPU scheduling
• - Knowledge of PII detection (Presidio) and LLM guardrails (NeMo Guardrails)