Urgently Looking For Ai Ml Engineer

AI/ML Engineer (Experienced 3-5 Years)

Job Summary

This AI/ML Engineer role requires minimum 3 years of experience and focuses on developing advanced AI systems in vision, speech, generative AI, and edge deployment, particularly using NVIDIA technologies. The position involves building real-time pipelines for video analytics, voice agents, and LLM-based applications, with backend integration and MLOps. It suits candidates with strong Python skills and expertise in computer vision, speech processing, and model optimization for edge devices like NVIDIA Jetson.

Key Responsibilities

• Speech AI / Voice Agent Development

  : Integrate ASR (Whisper, Riva), TTS (Coqui, Azure), LLM pipelines; handle wake-word detection, WebRTC streaming, and edge optimization on Jetson.

• AI/ML Model Development

  : Train models via TAO Toolkit, PyTorch/TensorFlow; optimize with TensorRT/ONNX; build OCR (EasyOCR) and generative models like Stable Diffusion.

• LLM, RAG & GenAI

  : Deploy Llama/Mistral via Ollama; implement RAG with FAISS/Chroma; perform SFT/LoRA tuning for conversational AI.

• Edge AI & NVIDIA Ecosystem

  : Optimize for Jetson using TensorRT, CUDA, TAO; integrate with Omniverse/Isaac Sim.

• Backend, Integrations & MLOps

  : Create FastAPI/Flask services; use MQTT/Kafka/WebSockets; deploy Dockerized microservices with logging/monitoring.

• Vision AI & Video Analytics

  : Develop pipelines with NVIDIA DeepStream, GStreamer, RTSP streams; implement YOLO, DeepSORT tracking, OpenCV processing, and face recognition analytics.

Required Skills

• Strong Python programming.
• Vision AI: YOLO, DeepStream, OpenCV, tracking.
• Speech AI: ASR/TTS, real-time audio.
• LLM/GenAI: RAG, SFT/LoRA, prompt engineering.
• NVIDIA stack: Jetson, TensorRT, TAO.
• Streaming: RTSP, WebRTC, GStreamer.
• Backend: FastAPI, MQTT/Kafka.
• Models: CNN, RNN, transformers.

Good-to-Have Skills

• NVIDIA Riva for speech.
• Cloud (AWS/GCP/Azure).
• MLOps (MLflow, Kubeflow).
• Embedded Linux (JetPack).
• Audio DSP basics.

Education Requirements

Bachelors or Masters in Computer Science, Electronics, AI/ML, or related field.

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