Opportunity Description
Description
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 monitoring
+ Develop, 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 serving
+ Own MLOps practices: experiment tracking (MLflow, W& B), model registry, CI/CD for ML, canary deployments, drift detection, an...
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 monitoring
+ Develop, 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 serving
+ Own MLOps practices: experiment tracking (MLflow, W& B), model registry, CI/CD for ML, canary deployments, drift detection, an...
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