AI/ML Engineer

The AI/ML Engineer will design, build, and deploy production-grade machine learning and AI systems that power core products and features. This role bridges cutting-edge research with reliable, scalable engineering, turning prototypes into high-performance services that run 24/7 in production.

Key Responsibilities:

Design and implement end-to-end ML pipelines: data ingestion, feature engineering, training, evaluation, deployment, and monitoringDevelop, optimize, and productionize models using PyTorch/TensorFlow/JAX (including LLMs, vision, multimodal, and custom architectures)Optimize inference for latency, memory, and cost (quantization, pruning, distillation, TensorRT, ONNX, vLLM)Integrate models into backend systems via REST/gRPC APIs, event-driven architectures, or real-time servingOwn MLOps practices: experiment tracking (MLflow, W&B), model registry, CI/CD for ML, canary deployments, drift detection, and observabilityCollaborate with data scientists to harden research prototypes into clean, tested, production-ready codeBuild and maintain retrieval-augmented generation (RAG), agentic workflows, and prompt-engineered systems when appropriate (LangChain, LlamaIndex)Continuously monitor, retrain, and improve live models to maintain performance and reliability