Artificial Intelligence Engineer

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Role Overview

deployments, and scalable backend services. You will play a key role in building, fine-tuning, and deploying AI-powered solutions (voice, NLP, automation) that power RxOne's next-gen patient engagement and clinical workflow intelligence platform.

Key Responsibilities

• Build, fine-tune, and optimize

  open-source LLMs

  , ASR/TTS models, and other ML components.
• Develop and maintain

  containerized ML pipelines

  using Docker & Kubernetes.
• Deploy inference services in

  cloud-native environments

  (AWS/GCP/Azure).
• Collaborate with product & engineering teams to integrate models into production systems (APIs/microservices).
• Monitor model performance, latency, accuracy, and cost-efficiency.
• Implement CI/CD workflows for ML model updates and secure deployments.
• Write clean, scalable, well-documented code.

Required Skills & Experience

• 12 years of experience in

  AI/ML engineering

  , MLOps, or backend engineering.
• Strong understanding of

  open-source models

  (HuggingFace, Whisper, Ollama, GPT-J, Llama, etc.).
• Hands-on experience with

  Docker, Docker Compose, Kubernetes

  .
• Experience deploying models with

  TensorRT, ONNX Runtime, or vLLM

  (plus point).
• Good knowledge of Python, FastAPI/Flask, and cloud services.
• Familiarity with GPU environments (NVIDIA, CUDA, inference optimization).
• Understanding of vector databases (Pinecone, Weaviate, Chroma) is a bonus.

Nice-to-Have

• Experience building

  voice AI pipelines

  (ASR, TTS, NLU).
• Exposure to

  observability tools

  (Prometheus, Grafana, Sentry).
• Knowledge of DevOps and CI/CD (GitHub Actions, GitLab CI).

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